• Attend and complete the part-time Data Science & AI Bootcamp as part of the apprenticeship • Contribute to software projects for your host company • Write clean, maintainable and testable code using modern frameworks and tools • Collaborate in sprint-based workflows and participate in code reviews • Support feature development, debugging, documentation, and QA processes • Build your portfolio of production-level work while growing your technical and collaborative skills • Receive ongoing mentorship from senior developers and product leaders

• Complete Flatiron School’s Software Engineering (full-time) and AI & Data Science (part-time) bootcamp programs • Contribute to real software projects during a paid apprenticeship with an employer partner • Collaborate in sprint-based workflows and participate in code reviews • Build a portfolio of production-level work • Receive mentorship from experienced engineers and product leaders

Role Description We are hiring an AI/ML Engineer to help manage, expand and oversee our rapidly growing portfolio of federal contracts. As an AI/ML Engineer, you’ll help design, build, and deploy machine learning models that improve how Veterans interact with digital services like VA.gov. You’ll collaborate with product managers, data scientists, and engineering teams to support initiatives such as: - Intelligent routing for support requests - Personalized content delivery - Anomaly detection - Natural language processing for virtual agents You’ll also play a key role in: - Data preparation - Model training - Evaluation - Performance monitoring All work must align with VA’s security, privacy, and equity standards. Qualifications - 3–5 years of experience in applied machine learning, data science, or AI engineering roles - Prompt engineering, agent orchestration, LLM evaluation, Python and backend API design - DevOps experience (for custom backend deployment help) - Proficiency in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, or Hugging Face Transformers - Experience building and deploying ML models in production using tools like Docker, MLflow, or SageMaker - Familiarity with data preprocessing, feature engineering, and working with structured and unstructured datasets - Understanding of NLP techniques, including intent classification, entity recognition, or sentiment analysis - Experience with Python, LangChain, LangGraph, and specific low-code platforms - Strong grasp of model evaluation, explainability, and fairness (especially in public service contexts) - Experience with either: Retool, Airtable integrations, Outsystems, Appian, n8n, Zapier, MS Power Automate - Ability to translate user needs and operational data into ML solutions that enhance Veteran experience - Excellent communication skills, including the ability to explain model behavior to non-technical stakeholders - Bonus: Experience working with healthcare data, VA systems, or federal AI/ML environments - Experience working in Agile development environments Requirements - Must be a US Citizen and able to work domestically - Must be able to attain low-level security clearance Education - Bachelor’s degree Benefits - Fully remote - Annual stipend - Comprehensive Benefits Package - Company Match 401(k) plan - Flexible PTO, Paid Holidays

At Reltio®, we believe data should fuel business success. Reltio’s AI-powered data unification and management capabilities—encompassing entity resolution, multi-domain master data management (MDM), and data products—transform siloed data from disparate sources into unified, trusted, and interoperable data. Reltio Data Cloud™ delivers interoperable data where and when it's needed, empowering data and analytics leaders with unparalleled business responsiveness. Leading enterprise brands—across multiple industries around the globe—rely on our award-winning data unification and cloud-native MDM capabilities to improve efficiency, manage risk and drive growth. At Reltio, our values guide everything we do. With an unyielding commitment to prioritizing our “Customer First”, we strive to ensure their success. We embrace our differences and are “Better Together” as One Reltio. We are always looking to “Simplify and Share” our knowledge when we collaborate to remove obstacles for each other. We hold ourselves accountable for our actions and outcomes and strive for excellence. We “Own It”. Every day, we innovate and evolve, so that today is “Always Better Than Yesterday”. If you share and embody these values, we invite you to join our team at Reltio and contribute to our mission of excellence. Reltio has earned numerous awards and top rankings for our technology, our culture and our people. Reltio was founded on a distributed workforce and offers flexible work arrangements to help our people manage their personal and professional lives. If you’re ready to work on unrivaled technology where your desire to be part of a collaborative team is met with a laser-focused mission to enable digital transformation with connected data, let’s talk! Job Summary: As a senior architectural leader within the Enterprise AI Hub, you will design and implement scalable AI systems aligned to Reltio’s enterprise AI strategy. You will partner with the Director, Enterprise AI to evolve the foundational architecture that enables secure, governed agentic workflows across the organization—helping to engineer the “Reltio Brain” (our Context Intelligence Operating System). In this role, you will evaluate cloud AI platforms, orchestrate vector databases, and help build the Model Context Protocol (MCP) gateways that securely connect AI to our corporate ecosystem. You will spend a meaningful portion of your time working directly with specialized AI Engineers to build the foundational primitives ("building blocks") that empower embedded AI Business Partners to innovate safely and rapidly. Job Duties and Responsibilities: Agentic Architecture & Orchestration: - Lead the application of advanced principles to design and develop the overarching architecture for multi-agent systems, moving beyond simple conversational RAG to deterministic, goal-driven planning loops. - Define how specialized agents communicate, delegate tasks, and maintain persistent state across complex business workflows using frameworks like LangGraph or CrewAI. Model Context Protocol (MCP) Governance: - Architect centralized MCP gateways. - Standardize how all internal agents securely discover, authenticate, and connect to enterprise systems (Salesforce, Reltio-on-Reltio, HRIS, Jira). - Eliminate bespoke API integrations in favor of a universal, auditable tool-calling ecosystem. Semantic Layer & Vector Infrastructure: - Enable the enterprise data grounding strategy with infrastructure design. - Establish advanced patterns for document ingestion, semantic chunking, and embedding model selection across the L1 (Personal), L2 (Team), and L3 (Enterprise) context hierarchy. - Select and optimize enterprise-grade vector databases (e.g., Pinecone, Milvus) for latency and recall accuracy. Deterministic Security & Access Control: - Implement rigid, deterministic software layers to govern probabilistic LLM outputs. - Design robust Role-Based Access Control (RBAC) and Attribute-Based Access Control (ABAC) mechanisms within the MCP layer to ensure strict data isolation and prevent sensitive context leakage or prompt injection attacks. Continuous Evaluation & Cost Optimization: - Partner with engineering leadership in the implementation and maturation of the Agentic Software Development Life Cycle (SDLC) - Implement continuous Agentic Evaluation (Evals) harnesses and LLM-as-a-Judge frameworks to monitor agent drift, hallucination rates, and silent failures in production. - Design intelligent model routing strategies (balancing frontier LLMs with Small Language Models) to optimize inference costs and throughput. Technical Leadership & Enablement: - Provide decisive architectural leadership, guiding complex technical decisions and ensuring alignment to enterprise standards. - Mentor a highly specialized pod of AI Engineers, enforcing rigorous systems-engineering standards. - Create formal networks and coordinate among groups within the organization, conveying AI capabilities to diverse stakeholders and assisting in translating them into measurable business ROI. Skills You Must Have: - Typically requires a minimum of 12 years of related experience with a Bachelor’s degree; or 8 years and a Master’s degree; or a PhD with 5 years experience; or equivalent experience. This must include progressive software architecture and distributed systems engineering, with a minimum of 2+ years exclusively focused on production-grade generative AI, LLM orchestration, and autonomous agent deployment. - Deep, practical mastery of the Model Context Protocol (MCP) and its implementation for secure, universal enterprise tool calling. - Advanced expertise in multi-agent orchestration frameworks (e.g., LangGraph, CrewAI, Semantic Kernel) and transitioning from basic scripting to fault-tolerant system design. - Authoritative knowledge of vector databases (Pinecone, Weaviate, Milvus), hybrid search architectures (dense/sparse retrieval), and advanced RAG optimization techniques at scale. - Strong security engineering mindset with the ability to build deterministic guardrails, data masking, and identity management (Okta/OAuth/RBAC/ABAC) over non-deterministic systems. - Command of modern AI observability and MLOps, including CI/CD for non-deterministic systems and tracing tools like LangSmith. - Extreme adaptability and a "builder" ethos: high tolerance for ambiguity and the agility to rapidly pivot architectures when the underlying foundation models or industry protocols evolve. Skills That Are Nice to Have: - Experience in a 500–2,000 employee cloud-native SaaS environment. - Experience working closely with core MDM, data engineering, or analytics teams. - Working knowledge of key business systems such as Salesforce, NetSuite, or Jira from a data-model and API-integration perspective. - Familiarity with local LLM deployment, SLM routing, or sandbox environment virtualization. - Prior involvement in setting up automated LLM evaluation pipelines (Evals). At Reltio, we carefully consider a wide range of compensation factors to determine your personal top of market. We rely on market indicators to determine compensation and your specific job family, background, skills, and experience to get it right. These considerations can cause your compensation to vary and will also be dependent on your location. Overall Market Range $132,000—$244,000 USD Reltio is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Reltio is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities.