Required Experience, minimum: 6 years
Required Experience, maximum: 12 years
Skills: AI, Analysis & Problem Solving, Machine Learning, Speech Processing, Natural Language Processing - NLP, Computer vision, Time Series Analysis, Cloud Computing, CI/CD Pipeline, Python
Minimum Qualification: B.Tech/B.E
Sr. AI Development Engineer
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6 to 12 years overall IT experience with 2+ years in Agentic AI and GenAI
What awaits you/ Job
SPOC
Profile
Team: FG-4 Quality AI Delivery Factory
Samuel Asha Kiran Tatapudi
Experience
- 8-10 years of professional experience in Artificial Intelligence, Machine Learning, Data Science, or Software Engineering, with a strong focus on Generative AI solution development and deployment.
- Proven experience designing, building, and deploying production-grade Agentic AI applications and multi-agent systems at enterprise scale.
- Demonstrated success delivering end-to-end AI solutions, from ideation and architecture through deployment, monitoring, and continuous improvement.
- Experience leading AI initiatives, collaborating with cross-functional stakeholders, and mentoring engineering teams.
Technical Skills
- Strong programming expertise in Python and modern software engineering practices.
- Hands-on experience with AI/ML frameworks and libraries including:
- PyTorch
- TensorFlow
- LangChain
- LangGraph
- AutoGen, CrewAI, or similar agentic AI frameworks
- N8N
- Deep understanding of:
- Large Language Models (LLMs)
- Generative AI architectures
- Prompt engineering
- Fine-tuning methodologies
- Retrieval-Augmented Generation (RAG)
- AI evaluation and guardrails
Cloud & DevOps
- Strong hands-on experience deploying, scaling, and operating AI applications on AWS and/or Azure.
- Experience working with:
- Amazon Bedrock
- Amazon SageMaker
- Azure OpenAI Service
- Azure Machine Learning
- EC2 / Azure Virtual Machines
- Cloud storage and networking services
- Expertise in containerized deployments using Docker and Kubernetes.
- Experience establishing and managing CI/CD pipelines using:
- Jenkins
- Github/Github actions
- GitLab CI/CD
- Azure DevOps
- AWS CodePipeline
MLOps & Production AI
- Strong experience implementing MLOps best practices, including model versioning, monitoring, observability, governance, and lifecycle management.
- Experience managing and optimizing AI systems in production environments, ensuring scalability, reliability, security, and performance.
- Familiarity with AI application monitoring, evaluation frameworks, and cost optimization strategies for cloud-based AI workloads.
Leadership & Collaboration
- Proven ability to lead technical design discussions and drive AI solution architecture decisions.
- Experience mentoring junior engineers and fostering engineering excellence within teams.
- Strong stakeholder management, communication, and presentation skills.
- Ability to operate effectively in a fast-paced, agile, and globally distributed engineering environment.
- Business fluent in English (written and spoken).
What should you bring along (Must have)
- 8 to 10 years IT experience; 2+ years GenAI development.
2+ years leading engineering teams or features.
- Python + FastAPI expertise.
- Experience with TensorFlow, PyTorch, LangChain, LangGraph, DSPy.
- Experience in Langgraph, langchain, n8n etc.
- RAG architecture implementation experience.
- Cloud (AWS/Azure), Docker, and Kubernetes exposure.
- Experience with n8n, MCP, and agent architectures.
What should you bring along (Good to have)
- Angular/JavaScript familiarity.
- Experience in automotive domain.
- LLM evaluation frameworks and safety practices.
- Knowledge graph and hybrid retrieval experience.
Bachelor’s or master’s in computer science, Data/AI, AI/ML or equivalent experience.
