About Workmates
Workmates is accelerating enterprise AI transformation across industries through cloud-first, AI-native solutions built on AWS. We partner with global enterprises to design, build, and operationalize intelligent systems that drive measurable business impact — from Generative AI and advanced ML to intelligent automation and data-driven decision platforms.
Role Overview
We are seeking a Head — AI/ML Delivery (AWS) to serve as the senior-most AI/ML delivery leader, owning the end-to-end execution of enterprise AI programs. This is a strategic, high-impact leadership role that combines deep technical mastery in AI/ML with executive-level client engagement, delivery governance, and practice-building responsibilities.
You will be the principal technical authority on AI delivery, responsible for translating AI strategy into scalable, production-grade solutions for enterprise customers. You will lead solution architecture, technical decision-making across multiple AI initiatives, team leadership, and client success — ensuring measurable business outcomes powered by AWS-native AI services and custom ML frameworks.
This role blends deep hands-on AI/ML expertise with strategic thinking, innovation leadership, and the ability to shape the technical direction of the entire AI delivery practice.
Location
Kolkata
Key Responsibilities
1. Client Delivery & Program Leadership
Lead end-to-end delivery of AI/ML and Generative AI programs across enterprise clients, ensuring scalability, maintainability, and tangible business value
Own solution architecture, delivery governance, timelines, risk management, and quality assurance for all AI engagements
Act as the executive escalation point and principal technical advisor to senior client leadership on AI capabilities, limitations, and strategic opportunities
Drive measurable business outcomes aligned with client KPIs and articulate ROI of AI investments
Build long-term client relationships and position Workmates as the trusted AI transformation partner
Manage multi-million-dollar delivery portfolios with P&L accountability
2. AI/ML Architecture & Technical Excellence (AWS Focused)
Architect scalable, production-grade AI solutions using AWS services including SageMaker, Bedrock,Strands,Kiro, Lambda, EC2, S3, Redshift, Step Functions, and the broader AWS AI/ML stack
Design and implement Generative AI solutions using LLMs, RAG pipelines, embeddings, vector databases, and agentic AI frameworks within the AWS ecosystem
Oversee the full ML lifecycle: data engineering, feature engineering, model training, fine-tuning, hyperparameter optimization, deployment, monitoring, drift detection, and continuous optimization
Establish technical standards and best practices for the entire data science and ML engineering practice, including model development, evaluation criteria, and deployment strategies
Design and implement novel machine learning approaches when standard solutions prove insufficient for complex business problems
Ensure high availability, performance, security, cost optimization, and responsible AI governance across all AI systems
Lead proof-of-concept initiatives for emerging AI technologies (e.g., multi-modal AI, autonomous agents) and assess their potential business impact
Implement comprehensive MLOps practices including CI/CD for ML, model versioning, A/B testing, and automated retraining pipelines
3. AI Strategy, Innovation & Research
Drive technical decision-making across multiple AI initiatives, providing expertise in selecting appropriate methodologies, frameworks, and approaches for different use cases
Lead research initiatives to explore cutting-edge AI techniques (reinforcement learning, multi-modal models, graph neural networks) and their practical enterprise applications
Develop frameworks and methodologies for evaluating and mitigating AI risks, including bias, fairness, explainability, and ethical considerations
Establish reusable AI accelerators, solution templates, and AWS-based reference architectures to accelerate delivery
Stay current with the AWS AI roadmap and proactively integrate new capabilities into delivery practices
Support pre-sales and solutioning for AI opportunities with technical thought leadership
4. Team Building & Practice Leadership
Build, lead, and scale high-performing AI delivery teams comprising Data Scientists, ML Engineers, Data Engineers, and Cloud Architects
Mentor and guide senior technical leaders, helping them grow their expertise and problem-solving capabilities
Establish delivery frameworks, engineering standards, code review practices, and a culture of technical excellence
Drive capability development and upskilling programs aligned with the evolving AWS AI ecosystem
Lead technical reviews and provide architectural guidance for complex AI solutions across multiple teams
Collaborate with enterprise architecture and product teams to ensure AI solutions align with broader technical strategies
Set up and operationalize AI Centers of Excellence (AI CoE) for clients and internal practice
Required Qualifications & Experience
12+ years of experience in technology delivery with at least 7+ years leading AI/ML programs at an enterprise scale
Deep, hands-on expertise in Machine Learning, Deep Learning, NLP, Computer Vision, and Generative AI with a proven track record of leading complex AI initiatives
Strong architectural experience with AWS cloud services and the AWS AI/ML stack (SageMaker, Bedrock, Lambda, Glue, Redshift, etc.)
Demonstrated experience deploying LLM-based solutions, RAG architectures, and agentic AI systems using AWS Bedrock or SageMaker
Proven experience managing large-scale enterprise AI implementations with multi-million-dollar delivery portfolios
Strong understanding of distributed systems, data engineering pipelines, and scalable ML infrastructure design
Advanced proficiency in Python and hands-on experience with TensorFlow, PyTorch, Scikit-Learn, Hugging Face, LangChain, and related frameworks
Comprehensive understanding of MLOps practices and experience designing end-to-end deployment architectures
Deep knowledge of AI ethics, responsible AI, fairness considerations, and regulatory compliance requirements
Outstanding executive communication skills with the ability to influence technical direction at CXO levels
Demonstrated success in building high-performing teams and mentoring senior technical staff
Master’s degree in Computer Science, AI/ML, Mathematics, Statistics, or related quantitative field (PhD strongly preferred)
What We Offer
Opportunity to shape the AI practice of a fast-growing enterprise AI company
Direct impact on high-profile AI transformation programs for global enterprises
Collaborative, innovation-driven culture with access to cutting-edge AWS AI technologies
Competitive compensation, performance bonuses, and leadership growth opportunities
Flexible work arrangements across Mumbai, Bangalore, and Hyderabad
