Sr Agentic Systems Engineer

We are looking for an experienced Agentic Systems Engineer who is passionate about designing building and productionizing intelligent autonomous systems powered by LLMs AI agents tool use and modern orchestration this role you will develop reliable agentic applications RAG pipelines and tool integrations within an established platform architectureconnecting AI agents to enterprise systems across multiple business use cases.

• Build and ship AI-powered applications using Python and/or working within established LLM orchestration frameworks (LangChain LangGraph etc.).
• Implement agentic workflows multi-step tool-using agents that call APIs vector stores and databases according to defined design patterns.
• Build and tune RAG pipelines for enterprise use cases.
• Integrate and extend NLP/NLU models prompt templates and embeddings for conversational classification and automation tasks.
• Build and maintain agent integrations with enterprise applications across multiple business use cases via REST APIs connector frameworks or MCP-style tool registries.
• Write and maintain test cases and evaluation harnesses for agent behavior tool-call accuracy hallucination rate and task completion.
• Implement evaluation frameworks and observability for LLM/agent systems including tracing prompt evaluation failure analysis and regression testing.
• Apply appropriate guardrails access controls validation and safety mechanisms to ensure agents operate within defined boundaries.
• Work with SQL/NoSQL databases to manage structured and unstructured data pipelines feeding agent workflows.
• Contribute to full-stack delivery connecting LLM backends to modern frontends.
• Operate within existing access-control logging and audit patterns for multi-tool agent systems; flag gaps to the architecture team rather than redesigning independently.

• 6 years of professional software engineering experience including at least 12 years hands-on building with LLMs or agentic frameworks.
• Strong proficiency in Python and/or for AI and backend development.
• Working knowledge of major LLM providers (e.g. OpenAI Anthropic) and prompt orchestration frameworks (LangChain LangGraph).
• Hands-on expertise in building LLM applications including
• Prompt engineering and enforcing structured outputs
• Tool integration and function calling
• Retrieval-Augmented Generation (RAG) using vector databases and embedding-based search
• Designing multi-agent workflows and orchestration frameworks
• Managing context windows and conversational state
• Experience integrating external tools and APIs via function calling or tool-registration mechanisms.
• Experience integrating agents or tools with enterprise SaaS applications via REST APIs or connector frameworks.
• Working knowledge of SQL and NoSQL databases and how they plug into AI pipelines.
• Experience writing test cases or evaluation harnesses for agent/LLM behavior (accuracy hallucination tool-call correctness).
• Familiarity with agent evaluation techniques including LLM-as-a-judge task-based evaluations benchmark design and automated regression testing.
• Understanding of access-control and audit-logging patterns in multi-tool multi-agent systems.
• Understanding of AI security prompt injection data leakage permission boundaries and agentic-system guardrails.
• Strong debugging skills and the ability to implement complex multi-step systems within an established architecture.

• Understanding of cloud deployment and infrastructure (AWS GCP).
• Knowledge of containerization and CI/CD pipelines (Docker GitHub Actions).
• Experience with AI observability guardrails and safety mechanisms for LLMs.
• Familiarity with data warehouses or analytical query engines for large-scale structured retrieval.