Junior AI Agent Engineer

(0–2 yrs • Full-Time • Remote-First)

Why this role?

autonomous agent chains

• Prototype task-specific agents:
• • “DPR Validator” – reads today’s WhatsApp DPR, checks BOQ limits, writes feedback.
• • “Incident Triage Bot” – summarises image/video evidence, suggests severity and next steps.
• Wire agents to tools: Vector-DB RAG, ERPNext REST, SQL, Python calculators, WhatsApp send-API.
• Add memory & state (Redis / Postgres) so agents recall project history and user preferences.
• Write automated evals (truthfulness, task-success %, latency) and push results to Grafana.
• Package each agent as a FastAPI micro-service; deploy via GitHub Actions → EKS-Fargate.
• Document prompt chains, tool specs, and failure modes in Markdown + Mermaid.

• 0-2 yrs industry

  or

  a solid portfolio of LangChain / LlamaIndex / CrewAI / AutoGen hacks.
• Python 3 (async/await basics) and Git fluency (branch → PR → merge).
• Basic knowledge of OpenAI / Bedrock / HuggingFace APIs and one vector store (FAISS, Pinecone, OpenSearch).
• Comfortable reading REST docs and gluing APIs together.
• Clear written English; you can turn messy experiment notes into a crisp README.

• Built a function-calling or tool-calling agent that actually shipped (Discord bot, Slack helper, side hustle).
• Exposure to Docker and simple CI (GitHub Actions).
• Familiar with evaluation frameworks (LangSmith, PromptLayer, ReAct eval notebooks).

• Day 30:

  first agent demo hits WhatsApp sandbox, returns correct answer in < 5 s.

• Day 60:

  agent container auto-deploys with CI; dashboards show < 1 % failed calls.

• Day 90+:

  you add memory + feedback loop that improves task-success by ≥ 15 %.

• Remote-first, async-friendly culture; meet quarterly for hack-weeks (company-paid).
• Competitive junior salary + GPU credit + conference / course stipend.
• Direct mentorship from our MCP Architect and Applied-AI Lead—fast feedback loops.

How to apply

and