Hello
Senior Agentic AI Engineer (Python)
Experience: 5 10 years
Location: Boston, MA
Primary Objective
We are seeking a Senior Agentic AI Engineer to design, build, deploy, and operate enterprise-grade AI agents and multi-agent systems. The role focuses on Generative AI, LLMs, agentic workflows, RAG architectures, AI orchestration, and governed enterprise AI platforms-delivering scalable copilots, intelligent automation, and knowledge systems across onshore and offshore delivery environments.
Success looks like: production-ready agents with measurable reliability, governed RAG integrated into enterprise systems, and clear observability/guardrails for business use cases.
Key Responsibilities
Primary
- Design, develop, and deploy AI agents and multi-agent workflows using Python and agentic frameworks (e.g., LangChain, LangGraph, or equivalent).
- Build enterprise-scale RAG solutions over structured and unstructured data sources.
- Develop agent orchestration workflows integrating models, tools, APIs, and enterprise services.
- Build AI-powered copilots, assistants, and automation solutions for enterprise use cases.
- Implement AI monitoring, observability, tracing, telemetry, and performance measurement.
Also expected
- Implement agent memory patterns (short-term, long-term, episodic).
- Integrate agents with enterprise platforms (APIs, databases, SharePoint, Confluence, Salesforce, knowledge repositories).
- Contribute to AI governance: guardrails, security controls, policy enforcement, and compliance.
- Optimize prompts, reasoning strategies, workflows, and execution performance.
- Collaborate with Data Science and ML teams on evaluation, optimization, and continuous improvement.
Must-Have Experience & Skills
- 5 10 years of software engineering experience with strong Python expertise.
- 3+ years designing and implementing AI/ML solutions.
- Hands-on experience building Generative AI applications using LLMs, RAG, and agentic frameworks (LangChain/LangGraph or equivalent; OpenAI SDK or similar).
- Experience delivering enterprise-grade AI solutions in production.
- Experience with distributed onshore/offshore team delivery.
- Solid API/service engineering fundamentals (REST/async services, integration patterns).
- Practical understanding of AI observability, evaluation, and production reliability.
Preferred Skills
- Cloud AI platforms (Azure OpenAI, AWS Bedrock, Google Vertex AI, or similar).
- Vector databases / search (pgvector, OpenSearch, Pinecone, Weaviate, or similar).
- LLMOps tooling (tracing, eval harnesses, prompt/version management).
- Enterprise integrations (SharePoint, Confluence, Salesforce).
- Containerized deployment practices (Docker; Kubernetes a plus).
- AI security, PII handling, and guardrail frameworks.
Soft Skills
- Clear written and verbal communication with technical and business stakeholders.
- Ability to own delivery end-to-end in a distributed team model.
- Pragmatic trade-off judgment between speed, quality, cost, and governance.
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