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Senior Associate & Summary

Job Title: AI Solution Developer – “AI-in-a-Box” Use Cases

Job Type: Full time

Experience Level: Mid to Senior

Role Level & Experience

- Senior Associate (SA): 5+ years of relevant experience in AI/ML, software engineering, or solution development
- Manager: 8–10 years of experience with demonstrated expertise in leading AI solution design, architecture, and delivery

About the Role We are looking for a skilled AI Solution Developer to design and deploy modular AI solutions as part of our “AI-in-a-Box” initiative. This role combines hands-on AI/ML development, solution architecture, and end-to-end lifecycle management.

You will work with advanced AI technologies such as LLMs, RAG pipelines, microservices, Vector Databases, and Knowledge Graphs to build deployable solutions (Activate, Deactivate, Remove) within client environments with ease.

Expected Areas of Responsibility

1. Solution Development & Engineering

- Design, develop, and deploy modular AI solutions using LLMs, RAG pipelines, and microservices
- Build scalable, reusable “AI-in-a-Box” accelerators for enterprise use cases
- Develop APIs and AI agents for use cases such as summarization, Q&A;, and chatbots

2. Architecture & Design

- Define end-to-end solution architecture including ingestion, retrieval, orchestration, and deployment
- Select appropriate models, embeddings, reranking strategies, and orchestration frameworks
- Ensure modular, extensible, and production-ready design

3. Stakeholder Collaboration

- Work closely with business teams to translate requirements into technical AI solutions
- Communicate complex technical concepts to both technical and non-technical stakeholders

4. Delivery & Lifecycle Management

- Manage the full lifecycle from PoC to production deployment and optimization




- Ensure scalability, reliability, and maintainability of deployed solutions

5. Platform Integration & Engineering

- Build data pipelines to ingest content from platforms like SharePoint and enterprise databases
- Integrate AI solutions with enterprise tools such as Outlook, Teams, and Salesforce
- Develop and deploy microservices using FastAPI/Flask

6. Performance Optimization & Monitoring

- Evaluate and improve retrieval accuracy, latency, and overall system performance
- Implement telemetry, logging, and evaluation frameworks
- Continuously optimize RAG pipelines and model performance

7. Governance & Responsible AI

- Ensure adherence to Responsible AI practices, including evaluation, testing, and compliance
- Maintain data security, privacy, and governance standards

Role Differentiation

Senior Associate (SA)

- Hands-on development and implementation of AI solutions
- Contribute to architecture design and technical problem-solving
- Execute development, testing, and deployment tasks
- Collaborate closely with team members and stakeholders

Manager

- Lead solution architecture and design decisions
- Own end-to-end delivery and client engagements
- Mentor and guide junior team members
- Drive best practices, standards, and reusable frameworks
- Manage stakeholders and ensure delivery timelines

Key Responsibilities

- Design and build modular AI solutions using LangChain, Semantic Kernel, or custom pipelines
- Develop APIs and AI agents for enterprise use cases




- Translate business requirements into scalable AI solutions
- Build ingestion pipelines and integrate enterprise data sources
- Implement embedding, reranking, and retrieval strategies for RAG pipelines
- Enforce structured outputs using Pydantic, function calling, or similar techniques
- Containerize and deploy solutions using Docker and CI/CD pipelines
- Monitor performance metrics and continuously improve system quality

Required Skills

- Strong Python skills with experience in AI frameworks (LangChain, Transformers, OpenAI SDK, LLaMA APIs)
- Hands-on experience with RAG pipelines, embeddings, and prompt design
- Familiarity with Knowledge Graphs (Apache Jena, SPARQL)
- Experience with Vector Databases (Pinecone, Chroma, etc.)
- Knowledge of embedding models (OpenAI Ada, Cohere, BGE/E5) and reranking techniques
- Experience building microservices (FastAPI, Flask)
- Exposure to multi-agent frameworks (LangGraph, CrewAI, AutoGen)
- Understanding of Model Context Protocol (MCP)
- Cloud experience with Azure (AKS, App Service, ACI) and DevOps tools
- Integration experience with enterprise platforms (Outlook, Teams, Salesforce)

Preferred Experience

- Delivery of at least 2 AI projects (PoC or production)
- Strong collaboration with business and technical stakeholders
- Knowledge of Responsible AI practices
- Experience in AI lifecycle management and packaging

Candidate Assessment Process (Optional) Hands-On Exercises

- Build a RAG pipeline using vector databases and OpenAI/LLaMA
- Integrate with enterprise applications (e.g., SharePoint to Outlook workflow)

Technical Interview

- Solution architecture walkthrough (RAG, MCP, agents)
- Deployment strategy and DevOps lifecycle
- Performance testing, telemetry, and troubleshooting

Travel Requirements Not SpecifiedJob Posting End Date

📌 Data Developer_ Senior Associate (Hyderabad)
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