Top Tech Jobs & Startup Jobs in Boston, MA

Design, build, and deploy agentic AI systems, orchestration pipelines, and RAG/knowledge retrieval services. Implement scalable backend services, observability, LLMOps practices, and integrations with code repositories and enterprise systems. Mentor engineers and ensure explainable, traceable AI for regulated federal healthcare environments.

Lead end-to-end front-end development for an enterprise Agentic AI platform. Design interactive, explainable UIs that render streaming LLM outputs, code citations, dependency graphs and authoring workflows. Build real-time experiences with WebSockets/streaming APIs, ensure traceability to source code, collaborate with AI engineers and designers, and drive accessibility, performance, and observability across a FedRAMP-aligned federal deployment.

Design, prototype, and productionize applied AI capabilities (LLMs, RAG, agents) to improve reasoning, explainability, and developer productivity. Optimize retrieval, embeddings, multi-agent workflows, and evaluation frameworks; build benchmarks and diagnostics. Collaborate with architects and engineers to ingest enterprise knowledge, refine semantic search, and transition experiments into FedRAMP-aligned production for federal healthcare modernization.

Design and build identity services for AI agents and enterprise systems: authentication/authorization (OAuth2/OIDC/JWT/SAML/mTLS), credential lifecycle, enterprise IdP integrations, secure agent access, developer-facing identity SDKs/APIs, auditability, and compliance alignment for FedRAMP/Zero Trust environments.

Lead AI architecture and strategy for enterprise AI transformation: design scalable platforms using LLMs, RAG, agentic AI, and advanced analytics; establish patterns, governance, and MLOps; guide teams from POC to production while aligning technical roadmaps with business objectives.

Lead technical customer engagements and guide cross-functional teams to design, build, and deploy enterprise-scale AI solutions. Provide architecture and program leadership for LLMs, RAG, ML, and cloud-native systems; establish engineering standards, CI/CD, observability, and AI governance; mentor engineers and support business development.

Lead customer-facing design, development, and deployment of AI-enabled software solutions. Translate stakeholder needs into scalable architectures, build production-quality code and APIs, implement CI/CD and observability, and mentor engineering teams. Drive solution discovery, technical leadership across projects, and adoption of modern AI/ML and DevOps practices to deliver mission-critical outcomes.

Support VA AI modernization by reverse-engineering VistA/MUMPS Prosthetics module functionality to extract business rules, document requirements, create user stories and process flows, and collaborate with stakeholders and technical teams during Agile delivery, testing, and modernization efforts.

Lead the BA practice for a VA prosthetics AI modernization program: extract and validate business rules from VistA/MUMPS, apply human-centered design, define BA methodology, review BA deliverables, liaise with VA stakeholders and governance, mentor BA team, align scrum team backlogs, ensure accessibility and VIP artifact readiness, and support change management and training.

Lead enterprise architecture for the VA Health Portfolio: develop solution blueprints, conduct workflow and technology assessments, create current and future-state system design artifacts, define interfaces and data exchanges, translate product strategies into implementation requirements, promote DevSecOps practices, update technology roadmaps, and advise stakeholders to optimize IT investments and sustain production systems.