Lead the full lifecycle of AI feature development from research, prototyping to production and continuous improvement with feedback from stakeholders for value extraction
Job Summary
Lead the full lifecycle of AI feature development from research, prototyping to production and continuous improvement with feedback from stakeholders for value extraction.
Develop iterative prototypes to validate AI concepts and regularly demo them to stakeholders via moving the prototype to production, gather feedback and translate the work into measurable value uplift with continuous improvements.
Collaborate with product teams, research teams and domain experts to identify high-impact use cases where AI can deliver tangible improvements, quantify ROI, and communicate results effectively.
Matching Summary
Lead the full lifecycle of AI feature development from research, prototyping to production and continuous improvement with feedback from stakeholders for value extraction.
Skills & Requirements
Must-have
Applied AI application development
Python, PyTorch, FastAPI, Langchain
Generative AI (LLMs, Multi Modal)
Docker, Kubernetes, GitLab CI/CD
RDBMS, Vector databases
Nice-to-have
LLM-centric agents, enterprise copilots
LangGraph, Semantic Kernel
LLM performance evaluation frameworks
Aerospace, Autonomous Systems domain
Key Requirements
6-10 years in software or ML engineering
At least 3 years in applied AI based application development
Strong proficiency in object-oriented programming
Hands-on with Docker, Kubernetes, GitLab CI/CD
Practical understanding of RDBMS, vector databases