Job Title: Senior GenAI Engineer Job Category: Information Technology Time Type: Full time Minimum Clearance Required to Start: Secret Employee Type: Regular Percentage of Travel Required: Up to 10% Type of Travel: Local * * * The Opportunity: Join our team as a Senior GenAI Engineer supporting Department of War PPBE (Planning, Programming, Budgeting, and Execution) applications. You'll build cutting-edge AI solutions that directly modernize how the DoW plans, programs, budgets, and executes critical defense operations. You’ll work with cross-functional teams to develop AI-enabled features, build intelligent document processing pipelines, and deliver data-driven analytics for mission-critical defense financial systems. While the bulk of this role focuses on generative AI, you will also apply traditional machine learning techniques for forecasting, anomaly detection, and trend analysis on budget and execution data. This role operates across both unclassified and classified environments. Responsibilities: - Design and develop AI-enabled features for PPBE applications using LLMs, GenAI, and agentic AI patterns - Build RAG pipelines over budget justification documents, appropriation language, execution data, and DoD directives - Implement agentic workflows using orchestration frameworks (LangGraph, Agno, Haystack, CrewAI) for multi-step budgeting tasks such as POM construction, BES preparation, and J-Book generation - Develop traditional ML models for budget execution forecasting, obligation rate anomaly detection, and spend trend analysis - Implement prompt engineering strategies and integrate AI/LLM APIs (OpenAI, Anthropic, Bedrock) - Architect full-stack AI features with reliable API integrations, error handling, and graceful degradation - Establish LLM observability (cost, latency, quality) and responsible AI guardrails (hallucination detection, output validation, CUI safeguards) - Maintain full-stack applications (including Web Application development using modern technologies such as React, TypeScript, NodeJS, Python, and .NET) - Address security vulnerabilities and ensure compliance with DoD cybersecurity standards - Participate in code reviews, CI/CD pipelines, and collaborative development workflows - Document technical implementations and stay current with AI and ML developments Qualifications: Required: - Active Secret clearance - IAT Level II - Security+ Certification within 90 days of hire date - Bachelor’s degree in Computer Science, Data Science, Mathematics, or related STEM field. Masters degree preferred. - Minimum of 10 years relevant experience - 7 years of experience with software implementation across all aspects of the SDLC - 1+ years experience developing generative AI / LLM-powered applications - Expert-level proficiency in Python; strong JavaScript proficiency - Experience with RESTful APIs and integrating AI/LLM APIs (OpenAI, Anthropic, Bedrock) - Experience with prompt engineering techniques (few-shot, chain-of-thought, system prompts) - Experience with LLM orchestration frameworks such as LangGraph, Agno, CrewAI, or similar - Experience with RAG architectures, agentic patterns, and vector databases - Strong understanding of ML fundamentals (supervised/unsupervised learning, model evaluation, feature engineering, NLP) - Experience with data analysis and ML libraries (pandas, NumPy, scikit-learn, or equivalent) - Experience with containerization (Docker) and at least one major cloud platform (AWS, Azure, or GCP) - Proficiency with Git version control and CI/CD pipelines - Strong written and verbal communication skills Desired: - Experience building predictive models for financial forecasting, anomaly detection, or resource allocation optimization - Experience with vector databases (Chroma, Weaviate, pgvector) and embedding models - Familiarity with LLM observability tools (LangFuse, LangSmith, Weights & Biases) - Understanding of responsible AI concepts: bias mitigation, hallucination detection, safety guardrails - Experience with AWS GovCloud, AWS Bedrock, or Azure OpenAI Service - Working knowledge of Kubernetes, Terraform or other IaC tools, and infrastructure automation - What You Can Expect: A culture of integrity. At CACI, we place character and innovation at the center of everything we do. As a valued team member, you’ll be part of a high-performing group dedicated to our customer’s missions and driven by a higher purpose – to ensure the safety of our nation. An environment of trust. CACI values the unique contributions that every employee brings to our company and our customers - every day. You’ll have the autonomy to take the time you need through a unique flexible time off benefit and have access to robust learning resources to make your ambitions a reality. A focus on continuous growth. Together, we will advance our nation's most critical missions, build on our lengthy track record of business success, and find opportunities to break new ground — in your career and in our legacy. Pay Range: There are a host of factors that can influence final salary including, but not limited to, geographic location, Federal Government contract labor categories and contract wage rates, relevant prior work experience, specific skills and competencies, education, and certifications. Our employees value the flexibility at CACI that allows them to balance quality work and their personal lives. We offer competitive compensation, benefits and learning and development opportunities. Our broad and competitive mix of benefits options is designed to support and protect employees and their families. At CACI, you will receive comprehensive benefits such as; healthcare, wellness, financial, retirement, family support, continuing education, and time off benefits. Since this position can be worked in more than one location, the range shown is the national average for the position. The proposed salary range for this position is: $90,300-$189,600 CACI is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, age, national origin, disability, status as a protected veteran, or any other protected characteristic.

Current Employees: If you are currently employed at any of the Universities of Wisconsin, log in to Workday to apply through the internal application process. Job Category: Academic Staff Employment Type: Regular Job Profile: Data Scientist III Job Summary: The Large Language Model (LLM) / Natural Language Processing (NLP) Engineer will serve as a hands-on technical contributor responsible for building, integrating, and operationalizing advanced language-model capabilities within the Wisconsin Health Data Hub (WHDH) platform. WHDH is a federally funded initiative developing a secure, cloud-native data ecosystem designed to support biomedical research, advanced analytics, and AI-driven discovery using real-world health data. This role focuses on the practical implementation of NLP and generative AI technologies that enable scalable analysis of large volumes of unstructured healthcare data such as clinical notes, research publications, and other text-based datasets. The engineer will design and deploy production-grade AI services, integrate LLM capabilities into the WHDH platform, and support researchers and partner organizations in leveraging these tools for applied healthcare analytics. The position requires a strong engineering mindset and the ability to translate emerging AI capabilities into reliable, scalable solutions operating within a secure research data environment. Key Responsibilities LLM & NLP Engineering - Design, implement, and maintain production-ready NLP pipelines for processing large volumes of unstructured healthcare and biomedical text data. - Fine-tune, deploy, and optimize large language models for domain-specific applications including clinical text analysis, semantic search, and automated summarization. - Develop services for entity extraction, concept normalization, document classification, and information retrieval from healthcare datasets. - Build reusable NLP components and APIs that can be integrated into analytics workflows across the WHDH platform. Platform Integration & AI Services - Integrate LLM and NLP capabilities into WHDH’s cloud-based data and analytics platform. - Develop scalable APIs and microservices that enable secure access to language-model capabilities by research teams and application developers. - Implement containerized services and deployment pipelines to operationalize AI models in production environments. - Work with teams to ensure NLP pipelines operate efficiently within large-scale distributed data processing environments. Applied AI Solution Development - Collaborate with platform engineers and domain experts to design AI-driven solutions that address real-world healthcare data challenges. - Translate emerging LLM capabilities into practical tools for clinical text processing, data enrichment, and knowledge extraction. - Rapidly prototype and iterate AI-enabled features that improve usability and accessibility of the WHDH data platform. - Support applied analytics initiatives that leverage LLM capabilities to enhance research workflows. Security, Data Governance & Responsible AI - Ensure all AI solutions comply with institutional data governance policies and healthcare data privacy requirements. - Implement safeguards for secure handling of sensitive healthcare text data within NLP workflows. - Support responsible use of generative AI technologies through appropriate monitoring, evaluation, and documentation practices. - Collaborate with platform security teams to ensure compliance with HIPAA-aligned infrastructure requirements It is anticipated that this position will be remote and requires work be performed at an offsite, non-campus work location. The position requires the finalist to reside within the State of Wisconsin or relocate to Wisconsin within a reasonable time frame from the start date of the position. Schedule is flexible within business hours of Monday through Friday 8:00a.m.- 4:30p.m. Key Job Responsibilities: - Prepares data sets for analysis including cleaning/quality assurance, transformations, restructuring, and integration of multiple data sources - Serves as an institutional subject matter expert and liaison to key internal and external stakeholders regarding data science best practices and methodologies and represents the interests of data science - Composes and assembles reproducible workflows and reports to clearly articulate patterns to researchers and/or administrators - Leverage modern NLP frameworks and LLMs to extract critical insights from unstructured clinical notes and reports, ensuring data quality and integrity through rigorous preprocessing. - Develop predictive models using retrospective real-world data to estimate disease risk, progression, and treatment effectiveness, while addressing bias and fairness. Design and execute rigorous hypothesis testing on observational datasets to validate research findings - Work closely with data governance and security to ensure compliance with privacy regulations (e.g., NIST, HIPAA) when working with healthcare data; and address bias and fairness issues in AI models when dealing with sensitive health data - Develop and implement informatics pipelines for the processing, integration, and harmonization of heterogeneous data sources - Identifies and implements or guides others in implementing appropriate data science techniques to find data patterns and answer research questions chosen by the lead researcher including data visualization, statistical analysis, machine learning, and data mining - Organizes and automates project steps for data preparation and analysis - Documents approaches to address research questions and contributes to the establishment of reproducible research methodologies and analysis workflows Department: School of Medicine and Public Health, Informatics and Information Technology, Wisconsin Health Data Hub. The Wisconsin Health Data Hub (WHDH) is a grant-funded initiative within the Office of Informatics and Information Technology (IIT) at the University of Wisconsin–Madison School of Medicine and Public Health. WHDH brings together a multidisciplinary team of technologists responsible for designing, implementing, and operating a secure data enclave that supports the responsible use of real-world health data for biomedical research. The WHDH team develops and manages a scalable data platform that enables researchers to efficiently access, integrate, and analyze large-scale health datasets from participating health systems. By providing advanced data services, governance frameworks, and analytical capabilities, WHDH accelerates the research lifecycle—from project conception and data acquisition to analysis and discovery—while ensuring compliance with applicable regulatory, privacy, and security requirements. Compensation: The starting salary/hourly wage for the position is $76,289 annually; but is negotiable based on experience and qualifications. Employees in this position can expect to receive benefits such as generous vacation, holidays, and sick leave; competitive insurances and savings accounts; retirement benefits. For more information, refer to the campus benefits webpage. ☒ SMPH Faculty /Academic Staff Benefits Flyer 2026 Required Qualifications: - 3 Years of full-time professional experience building or deploying NLP or machine learning solutions in production environments. (5 years preferred) - Strong programming experience in Python and familiarity with modern NLP frameworks such as Hugging Face Transformers, spaCy, PyTorch, or TensorFlow. - Experience working with large-scale data processing pipelines and distributed data environments. - Experience deploying AI models using containerization technologies such as Docker and orchestration frameworks such as Kubernetes. - Ability to design and build scalable APIs and backend services supporting AI-powered applications. Preferred Qualifications: - Experience working with biomedical or clinical text data. - Familiarity with healthcare data models and standards such as FHIR, OMOP, or UMLS. - Experience developing AI solutions in cloud environments such as AWS, Azure, or Google Cloud. - Experience with MLOps practices including model deployment, monitoring, and lifecycle management. - Familiarity with vector databases, embedding models, and retrieval-augmented generation (RAG) architectures. - Experience building generative AI applications using modern LLM frameworks. Education: PhD Preferred; Focus in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related technical field preferred. How to Apply: For the best experience completing your application, we recommend using Chrome or Firefox as your web browser. To apply for this position, select either “I am a current employee” or “I am not a current employee” under Apply Now. You will then be prompted to upload your application materials. Important: The application has only one attachment field. Upload the following documents in that field, either as a single combined file or as multiple files in the same upload area. • Cover letter required • Resume Your cover letter should address [how your training and experience aligns with the required and preferred qualifications listed above]. Application reviewers will rely on these written materials to determine which applicants move forward in the process. References will be requested from final candidates. All applicants will be notified once the search concludes and a candidate is selected University sponsorship is not available for this position, including transfers of sponsorship and TN visas. The selected applicant will be responsible for ensuring their continuous eligibility to work in the United States (i.e. a citizen or national of the United States, a lawful permanent resident, a foreign national authorized to work in the United States without the need of an employer sponsorship) on or before the effective date of appointment. This position is an ongoing position that will require continuous work eligibility. If you are selected for this position you must provide proof of work authorization and eligibility to work. The department will not be able to support a request for a J-1 waiver. If you choose to pursue a waiver and apply for our position, neither the UW nor UWMF will reimburse you for your legal or waiver fees. Contact Information: Cody Roekle, croekle@wisc.edu, 16082637676 Relay Access (WTRS): 7-1-1. See RELAY_SERVICE for further information. Institutional Statement on Diversity: Diversity is a source of strength, creativity, and innovation for UW-Madison. We value the contributions of each person and respect the profound ways their identity, culture, background, experience, status, abilities, and opinion enrich the university community. We commit ourselves to the pursuit of excellence in teaching, research, outreach, and diversity as inextricably linked goals. The University of Wisconsin-Madison fulfills its public mission by creating a welcoming and inclusive community for people from every background - people who as students, faculty, and staff serve Wisconsin and the world. The University of Wisconsin-Madison is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to, including but not limited to, race, color, religion, sex, sexual orientation, national origin, age, pregnancy, disability, or status as a protected veteran and other bases as defined by federal regulations and UW System policies. We promote excellence by acknowledging skills and expertise from all backgrounds and encourage all qualified individuals to apply. For more information regarding applicant and employee rights and to view federal and state required postings, visit the Human Resources Workplace Poster website. To request a disability or pregnancy-related accommodation for any step in the hiring process (e.g., application, interview, pre-employment testing, etc.), please contact the Divisional Disability Representative (DDR) in the division you are applying to. Please make your request as soon as possible to help the university respond most effectively to you. Employment may require a criminal background check. It may also require your references to answer questions regarding misconduct, including sexual violence and sexual harassment. The University of Wisconsin System will not reveal the identities of applicants who request confidentiality in writing, except that the identity of the successful candidate will be released. See Wis. Stat. sec. 19.36(7). The Annual Security and Fire Safety Report contains current campus safety and disciplinary policies, crime statistics for the previous 3 calendar years, and on-campus student housing fire safety policies and fire statistics for the previous 3 calendar years. UW-Madison will provide a paper copy upon request; please contact the University of Wisconsin Police Department.

About us: Founded in 2011, Modus is a global, fully remote team of world-class technologists who thrive in a collaborative, innovative environment. We’re a digital product engineering partner for forward-thinking businesses. Our global teams work side-by-side with clients to design, build, and scale custom solutions that achieve real results and lasting change, partnering with industry leaders including AWS, GitHub, and Atlassian. We were fully remote before it was cool! Recognized as one of the Inc. 5000 Fastest Growing Private Companies for nine years and a top remote work company by FlexJobs, we have helped some of the world’s largest brands deliver powerful digital experiences. As an award-winning Atlassian partner with a world-class team, we help organizations innovate and solve complex challenges for Fortune 500 companies and beyond, we want to hear from you. Opportunity! We are looking for a Senior Back End Engineer to join our engineering team and help clients design, build, and scale advanced data solutions. You will work on large-scale, production-grade data systems, support AI and machine learning initiatives, and translate complex datasets into meaningful insights that drive business and product decisions. This role requires strong technical depth, the ability to operate in research-heavy and ambiguous environments, and close collaboration with cross-functional teams across product, data, and validation functions. Requirements: - Strong professional experience with Python for backend development, including building scalable APIs and services. Bonus points for knowledge and experience with FastAPI. - Hands-on experience with AWS, particularly observability and telemetry services (CloudWatch Logs/Metrics, X-Ray), plus general familiarity with core services like Lambda, API Gateway, and S3. - Experience developing and maintaining AI/ML-powered features or integrations, including working with APIs, models, and/or data pipelines - Strong knowledge of the LLM ecosystem and experience working with multiple AI providers (Anthropic, OpenAI, Gemini, Bedrock, etc.) - Solid understanding of distributed systems design and building applications that scale across high-traffic environments - Care about observability, reliability, and creating tools that make other engineers' lives easier - Proficiency in writing automated tests (unit, integration, and end-to-end) to ensure code quality and reliability - Familiarity with containerization tools such as Docker and CI/CD pipelines - Knowledge of infrastructure as code and configuration management tools (e.g.,Terraform, or similar) - Strong understanding of Agile development methodologies and collaborative engineering practices - Ability to translate product requirements into scalable, production-ready solutions - Experience working in remote or distributed teams, with a strong communication and ownership mindset. You’ll Love: - Building scalable data systems that power AI and machine learning solutions - Working on complex, high-impact data initiatives with real-world scale - Collaborating closely with cross-functional teams to deliver meaningful outcomes - Raising the bar for data engineering and analytics best practices - Continuously learning and exploring modern data and AI tooling By joining our team, you’ll be part of a winning squad that plays to each other’s strengths and celebrates every success together. Apply now and show us you’ve got what it takes to take your consulting skills to the next level with Modus Create!

Industry/Sector Not Applicable Specialism Managed Services Management Level Senior Associate Job Description & Summary At PwC, our people in managed services focus on a variety of outsourced solutions and support clients across numerous functions. These individuals help organisations streamline their operations, reduce costs, and improve efficiency by managing key processes and functions on their behalf. They are skilled in project management, technology, and process optimization to deliver high-quality services to clients. Those in managed service management and strategy at PwC will focus on transitioning and running services, along with managing delivery teams, programmes, commercials, performance and delivery risk. Your work will involve the process of continuous improvement and optimising of the managed services process, tools and services. Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow. Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: - Respond effectively to the diverse perspectives, needs, and feelings of others. - Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems. - Use critical thinking to break down complex concepts. - Understand the broader objectives of your project or role and how your work fits into the overall strategy. - Develop a deeper understanding of the business context and how it is changing. - Use reflection to develop self awareness, enhance strengths and address development areas. - Interpret data to inform insights and recommendations. - Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements. LLM Integration & CI/CD Engineer API Integrations | CI/CD Pipelines | Release Engineering | AWS and Secure Delivery Purpose: Build, operate, and improve the integrations and deployment paths that keep AI workloads stable, supportable, and safely releasable. Role LLM Integration & CI/CD Engineer Level AC - Senior Tower AI Operations & Platform Support (AI Managed Services) Experience 6+ years in DevOps, release engineering, API integration engineering, or a similar L2/L3 support role Work Location Bangalore / Hyderabad, India (Remote) Key Platforms AWS, GitHub Actions / Jenkins / Azure DevOps, OpenAI / Bedrock integrations, ITSM and observability tooling Role profile Senior hands-on engineer who can troubleshoot integrations, operate CI/CD pipelines, and support controlled releases in an enterprise-managed-services model. Primary focus APIs and connectors, deployment pipelines, secrets and IAM, release governance, rollback readiness, and L2/L3 troubleshooting. Best fit Someone who can balance speed with control, understands why releases fail, and can drive issues to closure across engineering, platform, and security stakeholders. Role Summary As an LLM Integration & CI/CD Engineer, you will support the non-production to production path for in-scope AI services and integrations. You will help build and operate repeatable deployment patterns, investigate pipeline and connector failures, coordinate release readiness, and improve the reliability and maintainability of the integration landscape. We are looking for engineers who do not just deploy code, but can reason through operational risk, rollback paths, configuration dependencies, and stakeholder impacts. Key Responsibilities 1. Integration and connector engineering - Build, support, and troubleshoot API-based integrations across in-scope AI platforms and enterprise systems. - Implement resilient integration patterns such as retries, idempotency, error handling, timeouts, and operational telemetry. - Work through authentication, configuration, payload, and dependency issues across application and platform boundaries. 2. CI/CD and release operations - Build and maintain CI/CD pipelines for AI workloads and supporting services, with clear validation, promotion, and rollback steps. - Operate pipelines in line with change and release governance and support safe promotion through environments. - Standardize templates, checks, and reusable workflows to reduce release risk and improve consistency. 3. Secure delivery and operational readiness - Implement secure secrets handling, service-account management, and least-privilege access patterns for integrations and pipelines. - Coordinate release readiness activities including deployment plans, rollback paths, runbook updates, and post-release verification. - Support high-risk or time-sensitive changes in partnership with the incident commander and broader platform team. 4. Troubleshooting and continuous improvement - Provide L2/L3 support for pipeline failures, integration defects, and deployment-related incidents. - Drive corrective actions that improve supportability, reliability, and developer experience without weakening controls. - Maintain pipeline and integration documentation, escalation paths, and common-failure reference material. Preferred Skills and Experience Skill area Preferred background API and integration engineering Hands-on experience designing, supporting, and troubleshooting APIs, connectors, webhooks, and enterprise integrations. CI/CD and DevOps Experience building and operating CI/CD pipelines using tools such as GitHub Actions, Jenkins, Azure DevOps, or similar. Cloud deployment patterns Working knowledge of AWS services and deployment patterns for enterprise applications or AI workloads, including configuration promotion and operational validation. IAM and secrets management Experience implementing secure delivery practices using least privilege, secrets management, service accounts, RBAC, and approvals. Release and change governance Experience operating within ITIL-aligned incident, request, release, and change-management processes. Critical thinking and stakeholder engagement Ability to reason through ambiguous failures, synthesize technical and operational risk, and work effectively with platform owners, security teams, and business stakeholders. Nice to Have • Experience with Terraform or adjacent infrastructure-as-code tooling. • Familiarity with Bedrock, OpenAI, or other enterprise GenAI service integrations. • Experience supporting post-deployment validation, rollback exercises, and emergency changes. • Strong working knowledge of ServiceNow or similar ITSM tooling. Working Style & Core Behaviors - Approaches failures methodically and can separate symptom from cause. - Understands that stable delivery is as important as fast delivery. - Is comfortable driving follow-ups across multiple resolver groups and does not wait passively for answers. - Documents patterns and fixes so the team becomes less dependent on tribal knowledge. What Good Looks Like - Can diagnose whether a failed release is caused by code, config, IAM, pipeline logic, or environment drift. - Creates deployment patterns that are easy to support, easy to validate, and easy to roll back. - Improves integration resilience rather than repeatedly fixing the same class of issue. - Keeps change execution controlled while still helping the team move quickly. Team Context You will join PwC’s AI Operations & Platform Support team supporting clients’ run-state AI environment. The operating model is centered on Level 2 and Level 3 support, monitoring, incident response, service requests, minor enhancements, and continuous improvement across AWS/Bedrock, OpenAI, and related platform components. This role will work in a managed-services model focused on incident management, service requests, monitoring, minor enhancements, knowledge management, and continuous improvement. Success depends not only on technical skill, but also on ownership, collaboration, and the ability to engage stakeholders to progress work. Travel Requirements 0% Job Posting End Date