Analytica is seeking an AI Engineer to support an enterprise-wide modernization of AI capabilities for a high-profile financial regulatory client. This role centers on sustaining and enhancing AI systems deployed within Microsoft Azure-based data management and analytics platforms. Analytica has been recognized by Inc. Magazine as one of the fastest-growing 250 businesses in the US for 3 years. We work with U.S. government clients in health, civilian, and national security missions to build better technology products that impact our day-to-day lives. The company offers competitive compensation with opportunities for bonuses, employer-paid health care, training and development funds, and 401k match.   Key Responsibilities: - Provide operational support for enterprise AI capabilities, including onboarding users, managing access controls, triaging issues, and monitoring performance. - Maintain AI solution configurations in Azure, including role based access, usage tracking, and troubleshooting. - Support AI Innovation team's solutions, including AI systems deployed across multi cloud environments (Azure, Appian, Salesforce, ServiceNow, etc.). - Participate in CI/CD workflows using GitHub Enterprise; manage PBIs, bugs, and change requests. - Support continuous validation, security compliance, and Authority to Operate (ATO) requirements for AI systems. - Assist in implementing responsible AI monitoring, model evaluation, and improving AI user experience per agency governance guidance. Required Qualifications - Master's degree in Statistics, Mathematics, Computer Science, or related field. - 3+ years of experience in data and AI engineering roles, including operational support. - Experience with CI/CD and Agile work management tools such as GitHub Enterprise. - Experience with Infrastructure as Code, especially Terraform - Familiarity with Azure AI services, Azure Machine Learning, or cloud native AI operations. - Must be a US citizen - Must be able to obtain and maintain a Public trust security clearance. About ANALYTICA: Analytica is a leading consulting and information technology solutions provider to public sector organizations supporting health, civilian, and national security missions. Founded in 2009 and headquartered in Bethesda, MD, the company is an established SBA small business that has been recognized by Inc. Magazine each of the past three years as one of the 250 fastest-growing companies in the U.S.  Analytica specializes in providing software and systems engineering, information management, analytics & visualization, agile project management, and management consulting services. The company is appraised by the Software Engineering Institute (SEI) at CMMI® Maturity Level 3 and is an ISO 9001:2008 certified provider. Analytica LLC is an Equal Opportunity Employer. We are committed to providing equal employment opportunities to all individuals, regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other characteristic protected by applicable federal, state, or local law. As a federal contractor, we comply with the Vietnam Era Veterans' Readjustment Assistance Act (VEVRAA) and take affirmative action to employ and advance in employment qualified protected veterans. We ensure that all employment decisions are based on merit, qualifications, and business needs. We prohibit discrimination and harassment of any kind. Analytica LLC also provides reasonable accommodations to applicants and employees with disabilities, in accordance with applicable law. To enhance efficiency, fairness, and accuracy, Analytica may use AI-assisted tools to support certain aspects of our hiring process. - Application Review: AI tools may help identify skills and experiences relevant to the role. - Interview Support: AI-powered notetaking tools may be used during interviews to document discussions and summarize key points. These tools are used to assist our team. All hiring decisions are made by Analytica recruiters and hiring managers. By submitting an application, you acknowledge that AI-assisted tools may be used to support parts of the application and interview process. When receiving email communication from Analytica, please ensure that the email domain is analytica.net to verify its authenticity.

Role Description You can’t improve what you can’t measure. Every answer on Vera is a clinical decision being made by a clinician. That’s the bar. Not “mostly correct,” not “good on average.” We need to know exactly how the Vera behaves, where it holds up, where it breaks, and why. Think of the system like a chessboard with millions of different combinations. Different models, prompts, retrieval strategies, ranking, parameters, all interacting at once. Your job is to understand that space and push it in the right direction by optimizing every part of it, down to the smallest parameter. This isn’t about writing eval scripts and calling it done. It’s about going a step further, understanding how the system behaves across specialties, clinical contexts, and edge cases, and improving it so that answers hold up no matter the setting. You’ll be working on a complex search and reasoning engine, where the goal is simple but hard: make it better for every question, every specialty, every clinical setting. What You’ll Do - Optimize every layer of the system, from model behavior to retrieval to ranking to the smallest parameters - Take a system with thousands of moving parts and figure out which ones actually drive better answers - Push performance forward by testing, breaking, and refining how outputs are generated - Go deep on failures, not just what went wrong, but what pattern it reveals - Tune how the system behaves across different specialties, question types, and edge cases - Work directly with the founders on the highest-leverage improvements - Work with leading healthcare institutions to validate how the system performs in practice Qualifications - You don’t trust outputs you can’t explain - You care about being right, not just being close - You like working in messy spaces where there’s no obvious path - You move fast, but you don’t compromise when the stakes are high - You have strong technical depth in LLMs, search, or similar systems - You’re excited to work at the edge of what’s currently being done How we work - Ship, then improve. We get things in front of users fast and let real feedback drive iteration. A feature in production teaches you more than a month of planning. - Own it completely. There's no handoff culture here. You take a problem and see it through, from first principles to production. - Always look out for the user. Every decision comes back to the clinician on the other end. If it doesn't make their day better, it doesn't ship. Why Vera - Rocketship traction: 100%+ MoM growth, built by a team of 5 - Real impact: Every feature you build helps clinicians make better decisions and save lives - Best time to join: We’ve just raised our Series A and are entering the most important phase of the company, where a small team defines everything that comes next Details - Location: San Francisco (strongly preferred). For exceptional candidates, remote or relocation support (O-1A / H-1B sponsorship) available. - Compensation: Competitive salary + meaningful early-stage equity. Details shared in process. - Employment: Full-time

Role Description The AI Developer is responsible for designing and developing internal AI-driven applications and intelligent agents that support project management, procurement, reporting, and operational decision-making. This role focuses on building scalable AI-powered tools beyond simple automation, enabling the company to operate with structured intelligence across departments. Key Responsibilities - Design and develop internal AI-powered tools and dashboards to support automation and business operations. - Build and integrate AI models into structured workflows, ensuring scalability and system reliability. - Develop intelligent AI agents for summarization, forecasting, and workflow support with tool-calling capabilities. - Connect AI systems with internal databases, project management tools, and financial platforms for seamless integration. - Maintain system documentation, version control, and ensure performance monitoring and security standards. - Evaluate and implement emerging AI technologies while continuously improving system and agent performance through iteration and feedback. Qualifications - Degree in Computer Science, Engineering, AI, or related field preferred. - 3–5 years of experience in AI development, application building, or systems engineering. - Experience with AI agent frameworks and API integrations. - Strong understanding of structured data systems and workflow logic. - Fluent in English - written, spoken, and comprehension. - Strong analytical and architectural thinking skills. Benefits - Competitive salary. - Fully remote work arrangement with flexible working hours. - Annual performance bonus tied to KPIs. - Professional development budget for courses, certifications, and training. - Paid time off, including vacation and personal days. - Health and wellness allowance (fitness, counseling, or other approved programs). - Access to global company resources, systems, and cross-border collaboration opportunities.

• Design, develop, and evolve agents and workflows using MCP-based architectures • Build RAG pipelines and context retrieval mechanisms leveraging vector databases • Integrate agents with external APIs, tools, and services to execute complex flows • Develop agents in Python using Google ADK • Build and maintain agentive flows with LangChain and LangGraph • Integrate AI models and services via Vertex AI and Gemini models • Implement build, test, and deployment pipelines for agents and workflows • Define architecture standards, reusable components, and technical governance guidelines for the platform • Ensure solution observability through logs, metrics, and tracing • Partner with technical teams to ensure consistent integration between AI agents and enterprise applications • Design solutions aligned with business processes, integrations, and objectives • Ensure developed components are scalable, reusable, and prepared for continuous evolution