Job Description: AI Engineer (RAG & Agentic AI Specialist)
Work Location: Mumbai
Why would you like to join us
TransOrg Analytics specializes in Data Science, Data Engineering and Generative AI, providing advanced analytics solutions to industry leaders and Fortune 500 companies across India, US, APAC and the Middle East. We leverage data science to streamline, optimize, and accelerate our clients businesses. Visit at www.transorg.ai to know more about us.
Job Objective
To build enterprise-grade AI solutions that leverage Retrieval-Augmented Generation (RAG), Agentic AI frameworks, and large language models (LLMs). The candidate will be responsible for end-to-end solutioning using modern tools and platforms, interacting with business teams, and driving innovation within the Microsoft and Azure ecosystem.
Essential Job Tasks
- Build and deploy scalable AI solutions, from RAG systems to complex agent-based architectures using LangChain, CrewAI, AutoGen, or low code solutions like Copilot Studio, Azure AI Foundry.
- Leverage MCP, A2A, Microsoft Flows, and M365 Copilot for reasoning-based process automation.
- Collaborate with business to gather requirements and recommend best fit AI solutions.
- Work with the cloud infra team to set up secure, scalable AI systems on Azure.
- Ensure production-readiness and scalability of deployed AI solutions.
Areas of Responsibility
- End-to-end ownership of AI product delivery.
- Integration of AI agents and retrieval mechanisms.
- Enabling adoption and training of AI practice across the organization.
- Design, develop, and maintain backend services and APIs to support AI/ML applications at scale.
- Productionize ML and deep learning models, ensuring efficiency, reliability, and low-latency inference.
- Build scalable microservices and REST/gRPC APIs for deploying AI solutions in enterprise environments.
- Optimize AI model serving using frameworks such as TensorRT, ONNX Runtime, Triton Inference Server, or FastAPI.
- Implement MLOps practices including model versioning, monitoring, and automated deployments.
- Collaborate with AI researchers, data scientists, and product managers to translate prototypes into production-ready systems.
- Ensure robustness, fault tolerance, and security in backend AI systems.
- Integrate AI services with enterprise data platforms, cloud systems, and third-party APIs.
- Contribute to architecture discussions, design reviews, and performance tuning.
- Mentor junior engineers and contribute to best practices in AI software engineering.
Required Qualifications & Work Experience
- 2-5 years overall experience in AI/ML or related fields.
- 2-3 years hands-on experience in RAG and agentic AI solutions.
- B.E./B.Tech or M.Sc./B.Sc. in Computer Science, Data Science, or related field.
- Generative AI certifications are an advantage.
Technical Knowledge
- LangChain, CrewAI, AutoGen, Copilot Studio, Azure AI Foundry.
- Creation and deployment of APIs using FastAPI or similar frameworks.
- OpenAI, Hugging Face, GPT4 APIs.
- Azure cloud (preferred).
- Working knowledge of Databricks and Azure Synapse.
- Power Platform (Power Automate, M365 Copilot Chat).
- Agent workflow orchestration, prompt design, RAG architecture, vector databases.
- Strong proficiency in Python and backend frameworks (FastAPI).
- Expertise in Prompt engineering and working with various LLMs.
- Experience in productionizing AI/ML models with efficient inference pipelines.
- Hands-on experience with model deployment frameworks (Triton, TensorRT, TorchServe, ONNX Runtime).
- Knowledge of cloud platforms (Azure, GCP) and container technologies (Docker).
- Strong experience with microservices architecture, CI/CD pipelines, and monitoring tools (Prometheus, Grafana).
- Familiarity with databases (SQL/NoSQL) and scalable data storage solutions.
- Exposure to LLMs, SLMs, and GenAI model integration into backend systems is a plus.
- Understanding of security, authentication, and performance optimization in large-scale systems.
- Experience with version control (Git) and Agile development practices.
Other:
- Excellent problem-solving skills and attention to detail.
- Strong written and verbal communication skills in English.
- Ability to work collaboratively in cross-functional teams.
- Passion for building reliable backend systems that bring AI models into real-world impact.
