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AI/ML Developer
- Work Experience : 1-2 Years
- Work Mode : Onsite
- Number of Opening : 1
- Qualifications : Bachelor's in Computer Science or any related field
Job Description:
We are looking for a Junior AI Agent Engineer with 1-2 years of hands-on experience shipping AI agents or closely related autonomous systems. You will work directly on designing, building, and deploying multi-agent workflows that solve real customer problems end-to-end. This is a high-impact role with rapid growth potential, you’ll own significant parts of the agent stack from day one and collaborate closely with senior engineers and founding team members.
Responsibilities:
- Design and implement autonomous AI agents and multi-agent systems using frameworks like LangChain, LlamaIndex, CrewAI, AutoGen, or similar
- Build reliable tool-calling pipelines, memory systems (short-term & long-term), planning/reasoning loops, and evaluation frameworks
- Integrate agents with external APIs, databases, CRMs (Salesforce, HubSpot), browser automation (Playwright, Selenium), and internal tools
- Create robust evaluation suites (unit tests for agents, regression testing, human-in-the-loop eval, LLM-as-judge)
- Optimize agent latency, cost, and reliability in production environments
- Debug complex reasoning failures and hallucination issues in production agent runs
- Ship improvements to core agent infrastructure (routing, delegation, memory, retrieval, etc.)
- Collaborate with product and go-to-market teams to turn customer use cases into production agents
Requirements:
- 1-2 years of full-time or intensive project experience building AI agents or autonomous LLM-powered systems (side projects, internships, or previous roles all count if substantial)
- Strong Python proficiency and clean code practices
- Strong hands-on understanding of prompt engineering and chain-of-thought, RAG with vector databases, tool and function calling, agent memory design, and planning plus reflection patterns used in real-world AI systems
- Hands-on experience building AI agents using at least two major frameworks such as LangChain or LangGraph, LlamaIndex, CrewAI, AutoGen, Semantic Kernel, as well as custom agent loops built from scratch
- Experience putting agents into production (monitoring, logging, error handling, retries, cost controls)
- Familiarity with at least one cloud platform (AWS, GCP, or Azure) and basic DevOps (Docker, CI/CD a plus)
Nice-to-Have
– Contributions to open-source agent projects
– Experience with fine-tuning or training small models
– Background in reinforcement learning or multi-agent systems research
– Frontend skills (React/Next.js) for building agent interfaces
– Previous startup or 0→1 product experience
