Senior AI Engineer designing and building agent and RAG systems for NetBrain's network automation platform. Combining engineering with system - level thinking to enhance reliability and scalability.
About the role
- Senior AI Engineer developing production-grade AI and automation systems for NetBrain's network automation platform. Responsible for architecture, evaluation, scalability, and reliability in production.
Responsibilities
- Design and build core agent platform capabilities, including orchestration patterns (e.g., ReAct, Plan-and-Execute), tool execution layers, memory/context management, and guardrails
- Develop reusable agent skills and a standardized tool ecosystem aligned with platform conventions
- Implement enterprise-grade controls for agent execution, including human-in-the-loop workflows, permissioning, and policy enforcement
- Design and implement RAG services, including hybrid retrieval, reranking, embeddings, and citation behavior
- Define evaluation frameworks and quality metrics to ensure grounded, reliable outputs
- Build automated evaluation and regression pipelines to maintain quality at scale
- Establish observability (tracing, metrics, alerting) and optimize systems for latency, throughput, and cost
- Define best practices and incident response processes to ensure production readiness
- Prototype and productionize emerging approaches (e.g., GraphRAG, knowledge graphs, MCP integrations)
- Evaluate AI frameworks and infrastructure (e.g., LangChain, LangGraph, AutoGen, LlamaIndex) and guide platform decisions
- Diagnose and resolve complex AI system issues (retrieval quality, hallucinations, prompt regressions, agent failures)
- Lead system design and drive technical decisions through hands-on prototyping and benchmarking
Requirements
- BS in Computer Science, AI, Electrical Engineering, or related field (advanced degree preferred or equivalent experience)
- 5+ years of software engineering experience, including building and deploying production-grade LLM, agent, or RAG systems
- Proven track record of shipping and supporting AI-powered features in production
- Strong Python skills (API design, testing, error handling, environment management)
- Working proficiency in C# or C++
- Deep understanding of RAG system design and evaluation methodologies
- Experience building evaluation frameworks (test sets, metrics, regression pipelines)
- Understanding of LLM security risks (prompt injection, data leakage, agent misuse)
- Experience with graph databases, knowledge graphs, or GraphRAG preferred
- Experience designing human-in-the-loop systems and execution controls preferred
- Experience with agent frameworks (e.g., LangChain, LangGraph, AutoGen, LlamaIndex)
- You are able and willing to commute to our Burlington, MA headquarters twice a week on a hybrid schedule
Benefits
- 401k
- medical/dental coverage
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
AI Engineer developing production - ready AI solutions for business engagements. Collaborating with stakeholders to define high - value use cases on the Agentic AI platform.
Senior AI Engineer designing and delivering AI systems for Xelix, transforming financial controls through automation. Leading AI solutions combining machine learning and engineering practices in a fast - paced environment.
AI Engineer working on LLM - powered applications and AI systems at Zenith Insurance Company. Collaborating with teams to innovate and improve AI solutions in insurance and financial services.
AI Engineer for LLMOps & Evaluation at Auxilius.ai building AI solutions for Governance, Risk and Compliance. Own LLMOps pipeline and drive prompt engineering in a hybrid environment.
Senior AI Engineer at HyperFi managing AI program end - to - end. Leading GPU architecture decisions and integrating AI into user - facing flows.
Associate AI Engineer in LAUNCH program developing AI solutions. Collaborating with teams and working post - training on client projects.
AI Engineer responsible for developing AI - first products and designing agentic workflows. Collaborate across the tech stack to move ideas from concept to production.
Entry - level AI Engineer responsible for developing, testing, and deploying ML and LLM - based solutions. Supporting foundational engineering skills across AI spectrum in a hybrid work environment.
Senior Consultant delivering enterprise - grade AI solutions for business challenges. Collaborating with clients and teams at Pioneer Management Consulting to drive measurable outcomes.