Senior Technical Lead - AI/ML Practice

">Senior Technical Lead - AI/ML Practice

10-13 Years Noida

• aiml

Senior Technical Lead - AI/ML Practice

Experience: 10-13 years

Experience Requirements:

• 10-13 years of experience in AI, Machine Learning, Data Engineering, or Software Engineering.

• 4-6+ years in a hands-on Tech Lead role.

• Experience working in System Integrators, IT Services, or Consulting organizations highly preferred.

• Strong background in delivery-focused roles with ownership of end-to-end implementation.

Role Overview:

The Senior AI/ML Tech Lead is a hands-on technical leader responsible for building, leading, and delivering enterprise-scale AI, ML, and GenAI solutions on cloud platforms.

This role emphasizes hands-on development, technical decision-making, code quality, and team mentorship, while collaborating closely with architects, product owners, and stakeholders.

Key Responsibilities

•  **Hands-On Development G Technical Leadership**
  

• Design and hands-on implement AI/ML and GenAI solutions on AWS, Azure, or GCP.

- Lead development of:

o RAG pipelines, LLM orchestration, and GenAI workflows

oCore ML pipelines and MLOps foundations

• Actively contributes to coding, reviews, debugging, and performanceoptimization.

- Review and guide:

o Application code, ML pipelines, infrastructure, and deployment patterns

• Ensure adherence to engineering best practices and solution standards.

ML, AI G System Design

• Apply strong practical understanding of:

o Data Science, AI/ML algorithms, and model behaviour

o Model selection, evaluation, explainability, and bias considerations

• Design systems supporting:

o Real-time, batch, async, and streaming inference patterns

o Performance, cost, and scalability trade-offs

• Guide engineers on:

o Algorithm selection

o Architecture patterns and optimization techniques

MLOps, Deployment G Platform Engineering

• Implement and maintain MLOps pipelines, including:

o Model lifecycle management
o CI/CD pipelines for ML and LLM-based systems
o Monitoring, logging, observability, and governance

• Build and optimize inference systems with:
  oLLM routing and fallback strategies
  oCaching, autoscaling, and GPU utilization
  oSecure, compliant cloud deployment practices

Team Leadership G Ownership

• Lead and mentor a team of 4-8 engineers.

• Act as the first escalation point for complex technical issues.

• Drive sprint execution, technical planning, and delivery commitments.

• Ensure alignment between:
  o Technical design
  o Implementation quality
  o Delivery timelines

• Collaborate with internal and external teams on solution direction.

Solutioning

• Lead AI solutioning during presales with delivery-backed credibility.

• Create architecture diagrams, solution narratives, and cost estimates.

• Support RFP/RFI responses, client workshops, and technical presentations.

• Shape productized AI service offerings.

Required Skills G Experience Technical

Skills

• Strong hands-on experience building AI/ML solutions on GCP, AWS, or Azure.

• Deep experience with:

o LLMs, RAG architectures, and GenAI frameworks
o MLOps platforms and cloud-native ML deployments
oContainerization and microservices (Docker, Kubernetes)

• Solid understanding of:

o Cloud security, IAM, networking, and cost optimization
o Scalable and fault-tolerant system design

Leadership C Communication

• Experience leading technical teams while remaining hands-on.

• Strong client-facing and stakeholder communication skills.

• Ability to guide pre-sales, architectural trade-offs and decision-making.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.