Agentic AI Developer

Senior GenAI Engineer

About the Role

We are looking for a Senior GenAI Engineer with strong experience in building and delivering production-grade AI and Generative AI applications. The role involves designing end-to-end AI solutions, leading technical implementation, and mentoring teams while working closely with business and engineering stakeholders.

We are hiring for two domain-specific tracks:

• BFSI Track AWS: Strong hands-on experience in BFSI/Banking/Financial Services along with AWS-based AI/GenAI deployments is mandatory.
• HCLS Track – Azure: Strong hands-on experience in Healthcare/Life Sciences (HCLS) along with Azure-based AI/GenAI deployments is mandatory.

Key Responsibilities

• Lead the implementation and delivery of AI and Generative AI applications.
• Design end-to-end AI systems using commercial and open-source tools.
• Build and deploy LLM, RAG, and Agentic AI solutions for enterprise use cases.
• Translate business requirements into scalable AI-driven solutions.
• Collaborate with data engineering teams to ensure data quality, governance, and smooth data flows.
• Define reference architectures, technical roadmaps, and best practices for AI applications.
• Design and manage data ingestion pipelines, model training environments, CI/CD, and monitoring systems.
• Use cloud services and containerization to deploy and scale AI systems.
• Ensure scalability, reliability, security, and maintainability of AI solutions.
• Provide technical mentorship and conduct knowledge-sharing sessions.

Requirements

• 4+ years of experience in AI, Machine Learning, GenAI, or related roles.
• Strong hands-on experience building AI agents using LangGraph, AutoGen, or CrewAI.
• Strong proficiency in Python and ML/DL frameworks such as TensorFlow, PyTorch, or Keras.
• Solid understanding of Deep Learning and NLP, including Transformers, RNN, CNN, and LSTM.
• Hands-on experience with RAG, LLMs, vector databases, prompt engineering, and Agentic AI.
• Strong experience with REST APIs, GraphQL, microservices, distributed systems, and event-driven architectures.
• Experience with message brokers such as Kafka or RabbitMQ.

Domain & Cloud Requirements – Mandatory

BFSI Track – AWS

• 2–3+ years of hands-on BFSI/Banking/Financial Services domain experience.
• Experience working on BFSI use cases such as banking, payments, lending, insurance, risk, fraud, wealth management, or financial operations.
• Strong hands-on experience with AWS for AI/GenAI deployments.
• Experience with services such as AWS Bedrock, SageMaker, OpenSearch, S3, Lambda, EKS/ECS, or equivalent AWS AI services is preferred.

HCLS Track – Azure

• 2–3+ years of hands-on HCLS/Healthcare/Life Sciences domain experience.
• Experience working with healthcare providers, payers, health insurance, clinical, claims, or life sciences use cases.
• Strong hands-on experience with Microsoft Azure for AI/GenAI deployments.
• Experience with services such as Azure OpenAI, Azure AI Search, Azure ML, AKS, Azure Functions, and Azure Storage is preferred.

Candidates should have both the required domain experience AND the corresponding cloud experience for the track they are being considered for.

Good to Have

• Docker, Kubernetes, and CI/CD tools such as Jenkins or GitLab.
• SQL and NoSQL databases such as PostgreSQL, MongoDB, or Cassandra.
• Infrastructure as Code using Terraform or CloudFormation.
• Hands-on experience with Hugging Face, OpenAI APIs, LLaMA, and other LLM platforms.
• Experience with MLOps / LLMOps, model training, fine-tuning, and model evaluation.
• Experience with monitoring and logging tools such as Prometheus, Grafana, or ELK.
• Experience deploying production-grade GenAI/Agentic AI applications at enterprise scale.