Senior Software Engineer - AI

MCO (MyComplianceOffice)

Hyderabad

On-site

INR 2,500,000 - 4,200,000

Full time

2 days ago
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Benefits offered by this job

Flexible working arrangements
Opportunity for growth into leadership
Access to cutting-edge Gen AI tools
Continuous learning culture

Job summary

MCO (MyComplianceOffice) seeks an AI Senior Software Engineer to design and build Generative AI applications. You will own AI services end-to-end, integrating LLMs, RAG pipelines, and vector databases while collaborating across product, engineering, and business teams.

The role emphasizes production-grade AI systems, prompt engineering, and scalable deployment in a MEAN stack environment, with opportunities to grow into leadership as the team expands.

Qualifications

  • 3–8 years in software development with 1–2 years in Generative AI.
  • Hands-on production experience with LLM-powered apps using LangChain/LangGraph.
  • Experience with Hugging Face models and Transformers library.
  • Familiarity with RAG, vector databases, and embedding techniques.
  • Strong Python, API development, and testing practices.
  • Proficient in MEAN stack and API design (REST/GraphQL).
  • Git, CI/CD, and collaboration with product and stakeholders.

Responsibilities

  • Design, develop, and maintain LLM-powered features in Python using LangChain/LangGraph.
  • Build RAG pipelines with chunking, embedding, retrieval, and re-ranking.
  • Integrate Hugging Face models for generation, classification, and embeddings.
  • Develop robust prompt engineering and manage LLM context for production quality.
  • Create agentic workflows with LangGraph for multi-step reasoning and tools.
  • Expose AI features via Python APIs (e.g., FastAPI) for MEAN app consumption.
  • Uphold responsible AI practices and align with standards and governance.
  • Evaluate emerging Gen AI tools and add value to the product.

Skills

LangChain/LangGraph
Hugging Face
Python
FastAPI
REST APIs
GraphQL
MEAN stack
LLM/RAG pipelines
CI/CD
Vector databases
Prompt engineering

Tools

Pinecone
Weaviate
pgvector
MongoDB Atlas Vector Search

Job description

Job Description:

Job Description

We are looking for a skilled AI Senior Software Engineer to design and build Generative AI applications that solve real business problems. This is a Gen AI–first role: your primary work will be developing LLM-powered systems using frameworks like LangChain, LangGraph, and Hugging Face, with RAG pipelines, vector search, and prompt engineering at the core of what you do.

Our architecture separates AI services from the user-facing application. Your primary focus is owning the AI services end-to‑end — from model integration and inference pipelines through to production deployment. This split lets you go deep on AI while still maintaining visibility into how your work ships to customers.

You will collaborate with product managers, engineers, and business stakeholders to deliver AI features that create measurable value.

Job Requirements
  • 3–8 years of professional software development experience, with at least 1–2 years focused on Generative AI or LLM application development.
  • Hands‑on production experience building LLM-powered applications using LangChain and/or LangGraph.
  • Practical experience with Hugging Face — using pre‑trained models, the Transformers library, or the Inference API.
  • Working knowledge of RAG architectures, vector databases (e.g. Pinecone, Weaviate, pgvector, or MongoDB Atlas Vector Search), and embedding techniques.
  • Strong Python skills — writing clean, well‑tested, and maintainable code, ideally with experience in FastAPI or similar API frameworks.
  • Working proficiency in the MEAN stack: MongoDB, Express.js, Angular (17+), and Node.js.
  • Experience designing and consuming REST APIs; familiarity with GraphQL is expected for this role.
  • Comfortable using Git and working within modern CI/CD workflows.
  • Clear communicator who works effectively with both technical and non‑technical stakeholders.
Nice to Have
  • Experience deploying AI‑powered applications on any one of the cloud providers: AWS, Azure, or GCP.
  • Exposure to LLM evaluation frameworks, observability tools (e.g. LangSmith, Langfuse), or fine‑tuning workflows.
  • Prior experience integrating third‑party AI APIs (OpenAI, Anthropic, Bedrock, Cohere) in production.
  • Familiarity with MongoDB Atlas Vector Search or other native vector capabilities in operational databases.
  • Experience in an agile team environment with iterative product delivery.
Job Responsibilities
Generative AI Development (Primary Focus)
  • Design, develop, and maintain LLM-powered application features using Python and frameworks such as LangChain and LangGraph.
  • Build and maintain Retrieval‑Augmented Generation (RAG) pipelines — including chunking, embedding, retrieval, and re‑ranking strategies.
  • Integrate Hugging Face models and APIs for text generation, classification, embeddings, and semantic understanding tasks.
  • Develop and tune prompt engineering strategies, manage LLM context, and ensure reliable, production‑grade outputs.
  • Build agentic workflows using LangGraph — orchestrating tool use, multi‑step reasoning, and stateful agent behaviour.
  • Expose AI capabilities through clean Python APIs (e.g. FastAPI) that the MEAN application can consume.
  • Apply responsible AI principles, ensuring solutions are fair, explainable, and aligned with organisational and regulatory standards.
  • Evaluate and recommend emerging Generative AI tools, models, and frameworks that add tangible value to the product.
  • Contribute to the MEAN application (MongoDB, Express.js, Angular, Node.js), with a focus on integrating AI services into the product experience.
Engineering Excellence
  • You will also collaborate on the user-facing application — touching Node.js APIs, MongoDB, and Angular where needed to integrate AI capabilities — but the depth of ownership sits with the Python AI services.
  • Participate in code reviews to uphold quality and share knowledge across the team.
  • Troubleshoot and debug issues across the stack — from LLM response quality and retrieval accuracy to API performance and UI integration.
  • Contribute clear technical documentation for AI services, APIs, and integration points.
  • Work within agile/scrum delivery practices, collaborating closely with product managers and fellow engineers.
Job Benefits
  • A collaborative engineering team working on meaningful, real‑world Generative AI problems.
  • Opportunities to grow into senior and leadership roles as the team scales.
  • Access to cutting‑edge Gen AI tools, models, and a culture of continuous learning.
  • Flexible working arrangements and a commitment to work‑life balance.
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