Overview
Design, build, and maintain production-grade agent solutions as a hands-on Agent Engineer using Python, OpenAI Agents SDK, LangGraph, and LangFuse. Deliver features for multi-tenant services and support testing, CI/CD, security, observability, incident response, and operational excellence.
What you'll do
- Design, implement, and maintain production agent components in Python using OpenAI Agents SDK, LangGraph and LangFuse, following clean-code principles and team standards.
- Deliver features for multi-tenant services with built-in tenant isolation, baseline scalability, and secure defaults.
- Produce clear, testable user stories and decompose work into subtasks with measurable acceptance criteria.
- Write and maintain comprehensive unit tests and test automation; participate in mutation testing cycles and remediate identified gaps with guidance from senior engineers.
- Collaborate in Agile ceremonies, including backlog grooming, sprint planning, daily standups, and retrospectives.
- Deliver committed sprint work while surfacing risks early.
- Work with DevOps to maintain and improve CI/CD pipelines, automate routine deployments, add relevant test stages, and troubleshoot build/test failures.
- Participate in incident response and post-mortem activities by providing technical analysis, implementing remediation tasks, and documenting lessons learned.
- Incorporate information-security and data-privacy best practices in design, implementation, and code reviews.
- Monitor and improve observability by adding meaningful metrics, logs, and traces.
- Keep up to date with agent development patterns, testing techniques, and observability tooling and propose practical improvements.
- Provide constructive code review feedback and incorporate reviewer suggestions.
- Produce and maintain onboarding documentation, runbooks, and troubleshooting guides.
- Identify and implement small refactors and focused performance improvements, and escalate larger refactor or architectural changes for team prioritization.
- Fix broken builds, add automation for linting and tests, and improve pipeline reliability.
- Participate in technical interviews and candidate evaluations on request.
- Assist with benchmarking and profiling tasks and implement remediation under supervision.
- Ensure work aligns with the team vision and communicate impediments that could block delivery.
What you'll need
- BE/B.Tech, ME/M.Tech, or MCA.
- 5 to 8 years of experience.
- Proficiency with Python.
- Proficiency with OpenAI Agents SDK.
- Proficiency with RAG.
- Proficiency with Prompt Engineering.
- Proficiency with Context Engineering.
- Experience in benchmarking Evaluation sets and writing evaluators.
- Knowledge of Multi Agent Orchestration, including Worker (Supervisor) and Concurrent (Fan-Out/Fan-In).
- Skill Writing.
- MCP Implementation.
- Agent Security and Responsible AI.
- Direct experience with LangGraph and LangFuse in production environments.
- Strong technical knowledge.
- Excellent communication skills.
- Ability to work effectively within a team.
Nice to have
- Knowledge of Retail Planning Products.
- DevOps experience deploying agents with Performance, Scale, and Reliability in Production.
Details
Read the full description and apply on the company’s own careers page.