Job Title: Generative AI Engineer, Mid-level Job Category: Engineering Time Type: Full time Minimum Clearance Required to Start: None Employee Type: Regular Percentage of Travel Required: Up to 10% Type of Travel: Local * * * The Opportunity: Join CACI’s AI Enablement Team as a Generative AI Engineer delivering rapid, high‑impact AI solutions in 1–2 month engagements. You’ll build RAG pipelines, conversational AI platforms, and multi‑agent systems using our solution catalog, while helping program teams become self‑sufficient through hands‑on delivery and knowledge transfer. This role is ideal for engineers who enjoy variety, practical impact, and enabling federal mission teams to adopt AI effectively. Responsibilities: - Build and deploy production‑ready AI applications (RAG, conversational AI, multi‑agent systems) across short program engagements. - Implement GenAI solutions using vector databases, LLM orchestration frameworks, and managed AI services with strong observability and security practices. - Integrate LLM APIs and services into existing workflows; apply responsible AI guardrails; troubleshoot cloud and on‑prem integration issues. - Deliver workshops, documentation, and paired development to ensure teams can independently operate and extend AI systems. - Improve AI application templates and document emerging techniques based on field experience. - Validate program team readiness for independent AI operations. - Stay current with new GenAI tools and patterns and share insights with the team. Qualifications: Required: - 5+ years software engineering experience with strong Python and JavaScript; ability to build and maintain production systems using modern development workflows and Git. - Bachelor’s degree in Computer Science or a related major. - Ability to obtain a U.S. Secret Clearance. - Practical experience developing LLM applications, including agentic patterns, RAG, context engineering, vector databases, and observability fundamentals; familiarity with evaluation‑driven development and model routing. - Experience monitoring LLM performance, mitigating failure modes, and applying responsible AI practices (bias checks, guardrails, validation). - Strong API integration skills with REST and distributed systems. - Working experience with a major cloud provider (AWS/Azure/GCP), plus familiarity with Docker, CI/CD, IaC concepts, and core security practices. - Understanding of ML fundamentals relevant to LLM systems. - Ability to deliver quickly in unfamiliar environments and adapt to changing requirements. - Strong communication skills and experience creating clear technical documentation and explanations. - Pragmatic delivery mindset with sound architectural trade‑off judgment. - Active user of AI tooling and continuous learner in GenAI. - Experience with agile workflows (GitLab, Jira). Desired: - Experience building agentic systems with frameworks such as Agno, LangGraph, CrewAI, or OpenAI Agents; familiarity with LLM observability platforms and vector database technologies. - Cloud/infra depth (AWS Bedrock, GovCloud, Azure OpenAI, Kubernetes, Terraform, CI/CD automation). - Full‑stack development experience with modern frontend/back‑end frameworks. - Consulting or multi‑project experience supporting varied technical contexts. - Federal environment familiarity (DoD, NIST, ATO, FedRAMP). - Open‑source/community contributions, writing, or speaking. - Relevant technical certifications (Security+, AWS certs, etc.). - 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: $82,100-$172,400 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.

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 115,000 colleagues serve people in more than 160 countries. JOB DESCRIPTION: We’re focused on helping people with diabetes manage their health with life-changing products that provide accurate data to drive better-informed decisions. We’re revolutionizing the way people monitor their glucose levels with our new sensing technology. Working at Abbott At Abbott, you can do work that matters, grow, and learn, care for yourself and family, be your true self and live a full life. You’ll also have access to: - Career development with an international company where you can grow the career you dream of. - Employees can qualify for free medical coverage in our Health Investment Plan (HIP) PPO medical plan in the next calendar year. - An excellent retirement savings plan with high employer contribution - Tuition reimbursement, the Freedom 2 Save student debt program and FreeU education benefit - an affordable and convenient path to getting a bachelor’s degree. - A company recognized as a great place to work in dozens of countries around the world and named one of the most admired companies in the world by Fortune. - A company that is recognized as one of the best big companies to work for as well as a best place to work for diversity, working mothers, female executives, and scientists. THE OPPORTUNITY This AI Engineer position can work out remotely within the U.S. What You’ll Work On - Create Robust Metrics to Evaluate Next Gen AI Systems: Create robust metrics and validation plans to ensure that next generation systems do what they are hired to do - Develop Model Optimization Strategies for Next Gen AI Systems: Create and execute plans to improve AI/ML models - Data Analysis & Insights: Clean, analyze, and interpret complex health data from Continuous Glucose Monitors (CGM), smart insulin pens, and connected mobile apps. Identify trends, patterns, and key metrics to inform clinical research, product development, and patient health management. - Algorithm Development: Contribute to the development of machine learning algorithms for insulin titration adjustments and predictive models that improve diabetes outcomes. Collaborate with cross-functional teams to translate data insights into actionable clinical recommendations. Understand how to use data from CGM, connected insulin pens, and mobile app data to create next generation recommendation systems. - Clinical Management Product Research: Design and execute statistical analyses to evaluate the potential impact of clinical decision systems. Develop visualizations and technical documentation for research papers and presentations. - Data Pipeline Optimization: Build scalable and efficient data pipelines to integrate, clean, and process multi-source health data from legacy products to make this data available to our internal data scientists. Ensure high-quality data structures that support accurate and reliable analytics. - Collaboration & Communication: Partner with clinicians, product teams, and other stakeholders to develop next generation clinical decision systems that turn complex data into clear, actionable insights. Present findings effectively to both technical and non-technical audiences. Qualifications: - Master’s degree in Statistics, Data Science, or a related field (e.g., Computer Science, Mathematics, Bio Medical Engineering). A strong academic record is preferred. - Minimum 6+ years of experience in data science, preferably within the healthcare industry or related fields. Experience working with time-series data, clinical data, or medical devices is highly desirable. Experience dealing with real world data and creating machine learning and analytics from real world data is required. Experience in deploying at least one GenAI system to production is highly desirable. - Proficiency in Python (Pandas, NumPy, SciPy, SKLearn, TensorFlow), R, SQL (PostgreSQL, MySQL), and experience with cloud platforms like AWS or Azure. Ability to create production quality python code. - Statistical Expertise: Strong understanding of statistical concepts, including hypothesis testing, causal inference, and experimental design. In addition, evidence of creating statistical plans for the validation of GenAI systems in necessary. - Communication & Collaboration: Proven ability to work effectively in cross-functional teams and communicate complex technical concepts to diverse stakeholders. - Experience working with medical professionals and helping medical professionals interpret complex data is required. Preferred - Experience with diabetes management systems, CGM data, or insulin therapy optimization. - Publication record or presentations at conferences related to diabetes research or medical device analytics. - Familiarity with agile development methodologies and version control systems like Git. Apply Now Learn more about our health and wellness benefits, which provide the security to help you and your family live full lives: www.abbottbenefits.com Follow your career aspirations to Abbott for diverse opportunities with a company that can help you build your future and live your best life. Abbott is an Equal Opportunity Employer, committed to employee diversity. Connect with us at www.abbott.com, on Facebook at www.facebook.com/Abbott and on Twitter @AbbottNews and @AbbottGlobal The base pay for this position is $99,300.00 – $198,700.00In specific locations, the pay range may vary from the range posted. JOB FAMILY: Product Development DIVISION: ADC Diabetes Care LOCATION: United States of America : Remote ADDITIONAL LOCATIONS: WORK SHIFT: Standard TRAVEL: Yes, 10 % of the Time MEDICAL SURVEILLANCE: Not Applicable SIGNIFICANT WORK ACTIVITIES: Continuous sitting for prolonged periods (more than 2 consecutive hours in an 8 hour day), Keyboard use (greater or equal to 50% of the workday) Abbott is an Equal Opportunity Employer of Minorities/Women/Individuals with Disabilities/Protected Veterans. EEO is the Law link - English: http://webstorage.abbott.com/common/External/EEO_English.pdf EEO is the Law link - Espanol: http://webstorage.abbott.com/common/External/EEO_Spanish.pdf

• Serve as a technical authority for Generative AI and AI-driven architecture across the enterprise, providing hands-on architectural leadership as an individual contributor • Drive GenAI strategy and solution design, identifying, evaluating, and applying emerging technologies such as Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, vector databases, prompt engineering frameworks, and model orchestration platforms • Architect and govern Model Context Protocol (MCP) implementations, defining how context, memory, tools, policies, and guardrails are structured, versioned, and securely shared across AI workflows • Design and lead multi-agent and agent-to-agent orchestration architectures, enabling autonomous task decomposition, collaboration, escalation, and decision-making across AI agents and enterprise systems • Define orchestration strategies coordinating LLMs, agents, tools, workflows, and downstream systems, balancing performance, cost, reliability, observability, and maintainability • Partner with business and product stakeholders to translate business problems into AI-driven solutions, articulate technology value propositions, and support business-case development with measurable outcomes • Lead architectural discovery and design workshops, aligning AI capabilities with DIRECTV’s strategic goals and guiding teams toward practical, scalable implementations • Establish reusable AI architecture patterns, reference architectures, and best practices that accelerate adoption while ensuring consistency, governance, and risk management • Ensure architectural flexibility and future-proofing through modular, abstracted designs that support evolving models, vendors, and regulatory requirements • Influence enterprise standards for AI architecture, modeling practices, design principles, security, data governance, and responsible AI usage • Provide architectural guidance to delivery teams, reviewing designs, validating implementation approaches, and ensuring adherence to enterprise and AI-specific standards

• Lead the team through architecture, implementation, production launch, and fast iteration. • Stay hands-on: review designs and code, inspect traces, debug production behavior, evaluate prototypes, and help engineers make pragmatic tradeoffs. • Translate Agent OS strategy into concrete platform slices that ship quickly without creating one-off agent implementations. • Define platform contracts for role shells, capabilities, tools, actions, approvals, context, memory, evidence, and evaluation. • Drive evaluation as part of everyday engineering: scenario design, regression suites, trace review, simulation, production monitoring, quality gates, and rollout criteria. • Hire, coach, and retain strong engineers who can build fast, reason deeply, and operate responsibly in a fast-moving AI environment.