AI Engineer

Posted 3 Days Ago
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Hyderabad, Telangana, IND
In-Office
Mid level
Artificial Intelligence • Information Technology • Software • Consulting
The Role
Build and own production agentic AI solutions across concurrent projects using LangGraph and AWS AgentCore. Develop RAG pipelines, Python APIs, AI automations, and multi-model integrations; deliver POCs and production components while monitoring, debugging, and optimizing systems. Collaborate on architecture, evaluate retrieval quality, use pro-code and low-code approaches, and mentor associate developers through reviews and pair programming.
Summary Generated by Built In

Role Summary:

You build and own assigned solution streams across 1–2 concurrent projects. You implement agentic AI solutions on AWS AgentCore and LangGraph, contribute to POC delivery, and take full ownership of your components in production — including Pro Code builds and Low Code automations where the use case fits.


Key Responsibilities:

  • Agentic AI Development
    • Implement LangGraph agentic workflows on AWS AgentCore — state graphs, tool orchestration, conditional routing, error recovery.
    • Build custom RAG pipelines end-to-end: chunking strategy, embeddings, vector retrieval, accuracy evaluation.
    • Contribute to rapid POC delivery alongside the Architect and Lead.
    • Write production-grade Python with FastAPI, Pydantic, testing, and proper error handling.
    • Use AI coding tools (Claude Code, GitHub Copilot, Cursor, Cline) to accelerate builds. Own and fix all generated code in production.
  • Low Code & Automation
    • Build Low Code automations using Microsoft Copilot Studio and Power Automate when use case and bandwidth allow.
    • Understand Pro Code vs Low Code trade-offs — flag where Low Code is the better fit.
    • Stay current on Low Code platform capabilities as they expand rapidly.
  • Production Ownership & Collaboration
    • Own assigned components in production — monitor, debug, optimise, iterate.
    • Debug agent failures independently: context issues, tool errors, hallucination, retrieval degradation.
    • Collaborate with the Lead on architecture translation and implementation planning.
    • Mentor Associate Developers through code reviews and pair programming.


Required Skills & Experience:

Must Have:

    • LangGraph — State graphs, conditional routing, checkpointing — primary framework, non-negotiable.
    • LangChain — Chains, memory, custom tools — solid foundational knowledge.
    • AWS AgentCore — Hands-on preferred; strong LangGraph depth with ramp path acceptable.
    • AWS Bedrock — Model invocation, knowledge bases, guardrails.
    • Database & AI Data Access — SQL proficiency, NL-to-SQL, LLM-powered query and insight patterns. Snowflake a plus.
    • RAG Pipelines — End-to-end: chunking, embeddings, retrieval, evaluation.
    • Vector Databases — Pinecone, ChromaDB, OpenSearch, or FAISS — hands-on with at least one.
    • Python — Production-quality — type hints, async/await, FastAPI, Pydantic.
    • Multi-Model — OpenAI, Claude, Gemini, Llama — understand trade-offs across providers.
    • Pro Code vs Low Code — Copilot Studio and Power Automate — build when use case fits.
    • AI Development Tools — Claude Code, GitHub Copilot, Cursor, or Cline — accelerate delivery; own and fix all generated code.
    • Experience — 3–5 years total; 1–2 years GenAI/LLM; 6–12 months LangGraph; 2–3 projects with working code.

Good to Have:

    • AWS AgentCore Deep — Runtime, Memory, Tools Gateway hands-on.
    • MCP / A2A — Server/client implementation or protocol awareness.
    • Enterprise Integration — SAP HANA, Salesforce connectors.
    • Document Intelligence — OCR, layout-aware chunking.
    • Evaluation Frameworks — RAGAS, Promptfoo, DeepEval.
    • Certifications — AWS, GCP, or Azure AI/ML.


What We Expect From You

  • Customer Obsession
    • Proactively understand customer goals and deliver measurable value.
  • Competitive Drive
    • Set high standards, demonstrate tenacity, and ensure our solutions lead in quality.
  • Challenging Mindset
    • Foster fact-based dialogue, challenge assumptions, and encourage disruptive thinking.
  • Action and Learning Velocity
    • Build fast, fail fast, learn fast. Iterate rapidly and make data-driven decisions.
  • Collaboration and Accountability
    • Collaborate across a global team with humility, ownership, and mutual accountability.


Why Join Us?

    • Build production agentic AI at global scale — real systems, real impact.
    • Work with AWS AgentCore, LangGraph, MCP, A2A, and AI-powered development tools.
    • Operate in a high-trust team where Architect, Lead, Developer, and Associate work in sync.
    • A culture of rapid learning, fast iteration, and genuine technical excellence.

 



Skills Required

  • Hands-on LangGraph experience, including state graphs, conditional routing, and checkpointing
  • Solid LangChain knowledge, including chains, memory, and custom tools
  • AWS AgentCore experience or strong LangGraph experience with ability to ramp up
  • AWS Bedrock experience with model invocation, knowledge bases, and guardrails
  • SQL proficiency, including NL-to-SQL and LLM-powered query patterns
  • End-to-end RAG pipeline experience, including chunking, embeddings, retrieval, and evaluation
  • Hands-on experience with at least one vector database: Pinecone, ChromaDB, OpenSearch, or FAISS
  • Production-quality Python experience with type hints, async/await, FastAPI, Pydantic, testing, and error handling
  • Understanding of multiple AI model providers, including OpenAI, Claude, Gemini, or Llama
  • Experience with pro-code and low-code approaches, including Microsoft Copilot Studio and Power Automate
  • Experience using AI development tools such as Claude Code, GitHub Copilot, Cursor, or Cline
  • 3–5 years of total experience
  • 1–2 years of generative AI or LLM experience
  • 6–12 months of LangGraph experience
  • Experience delivering 2–3 projects with working code
  • Deep AWS AgentCore experience with Runtime, Memory, or Tools Gateway
  • MCP or A2A implementation experience or protocol awareness
  • Enterprise integration experience with SAP HANA or Salesforce connectors
  • Document intelligence experience, including OCR or layout-aware chunking
  • Experience with RAGAS, Promptfoo, or DeepEval
  • AWS, GCP, or Azure AI/ML certification
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The Company
HQ: Hyderabad
Year Founded: 2021

What We Do

AlgoLeap specializes in AI-powered software solutions, digital product engineering, and IT consulting services, focusing on digital transformation and AI-driven innovation.

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