
Generative AI/ML Lead
2 days ago
Job Description
Role Summary
We are looking for a
Generative AI/ML Lead
with advanced
cloud architecture expertise
, deep knowledge of
RAG and agentic AI patterns
, and hands-on leadership in delivering enterprise-grade AI solutions. This role combines
strategic vision
with
technical depth
, leading a team of engineers to implement AI-powered applications at scale, including
edge and hybrid deployments
.
Key Responsibilities
- Strategize
GenAI or ML solution architecture
across cloud, edge, and hybrid environments. - Experience in evaluating LLM applications and developing observability frameworks
- Research and implement latest technology and frameworks
- Experience working with diffusion models like Stable Diffusion, MidJourney, Runway, Imagen, Veo etc.
- Experience in working with structured data along with LLMs frameworks
- Lead design and implementation of
RAG-based
knowledge systems and
agentic AI workflows
. - Select and integrate
enterprise-grade AI models
(OpenAI, Anthropic, Mistral, LLaMA, custom fine-tuned models). - Drive
cloud-native AI deployments
leveraging AWS, Azure, and GCP AI services. - Architect
LLMOps
pipelines for scalable AI model lifecycle management. - Implement
AI governance, risk management, and compliance frameworks
for regulated industries. - Lead
PoCs and pilots
, then guide them to production-grade rollouts. - Evaluate and optimize
AI cost, performance, and security
trade-offs. - Mentor and manage AI engineers, setting
best practices for RAG, agentic, and edge AI
. Be responsible and own delivery outcomes for all GenAI initiatives, ensuring scope, timelines, and quality targets are met. - Collaborate with business stakeholders to
translate needs into AI-powered products
. - Establish
AI monitoring and observability
(drift detection, hallucination tracking, usage analytics).
Required Skills
- 8–15 years of technology experience, with
4+ years in AI/ML
and
2+ years in GenAI
. - Proven leadership in
cloud AI architectures
(AWS Bedrock/SageMaker, Azure OpenAI, GCP Vertex AI). - Strong expertise in
RAG architectures, embeddings, and semantic search
. - Experience in
agentic AI frameworks
(LangGraph Agents, Autogen, CrewAI, OpenAI/Google Agent SDK). - Advanced knowledge of
vector stores, distributed search, and multi-modal AI
. - Proficiency in
edge AI deployments
and low-latency AI inference optimization. - Expertise in
cloud networking, identity, and security
for AI workloads. - Strong understanding of
AI product lifecycle
, from ideation to production. - Excellent
stakeholder management
and
team leadership
skills. - Step in as a
hands-on problem solver
to debug, optimize, or redesign solutions when engineers encounter roadblocks. - Conduct
code and architecture reviews
to maintain engineering excellence.
Preferred Skills
- Experience in build, test and deploy various ML models
- Experience in building MCP, A2A protocol
- Experience with
AI marketplaces and model hosting
. - Multi-cloud AI cost optimization strategies.
- Contributions to
AI architecture standards
in enterprise settings.
-
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