Teamhead – AI & Machine Learning

Aimlroles; Bengaluru; On-site; INR 7,000,000 - 9,000,000; Full time

Job summary

Aimlroles is seeking a senior AI leader to own the AI/ML strategy and roadmap for enterprise solutions in Bengaluru. You will lead a diverse team of AI engineers, data engineers and scientists, driving architecture, development and deployment of scalable AI platforms.

You will define standards for GenAI, MLOps practices, and security while partnering with business leaders to translate complex challenges into data products with measurable ROI.

Qualifications

• 12+ years in AI/ML, data platforms or enterprise product engineering.
• 5+ years leading cross-functional technical teams.
• Proven track record building enterprise AI/ML products in production.
• Deep knowledge of ML lifecycle, governance and model monitoring.
• Experience with LLMs, transformers, RAG pipelines and prompt engineering.
• Exposure to cloud ecosystems (Azure, AWS, GCP) and cost optimization.

Responsibilities

• Define and own the enterprise AI/ML strategy with a multi-year roadmap.
• Lead and scale a cross-functional team of engineers and data scientists.
• Architect and oversee enterprise AI solutions including LLM-based systems and data-heavy apps.
• Drive full AI product lifecycle from discovery to value realization.
• Establish reference architectures, reusable frameworks and deployment patterns.
• Ensure MLOps maturity with CI/CD, monitoring, drift detection and governance.

Skills

AI strategy

Team leadership

Cloud platforms

MLOps

LLMs & RAG

Data architectures

Architecture discussions

Communication

Education

B.Tech / M.Tech / MS

MBA (plus)

Tools

Databricks

Spark

Delta Lake

CI/CD for ML

MLOps frameworks

Job description

YOUR MISSION

• Define and own the enterprise AI, ML strategy, building a multi-year roadmap aligned to digital and business transformation priorities
• Lead and scale a high-performing team of AI Engineers, MLOps Engineers, Data Engineers, Application Engineers and Data Scientists
• Architect and oversee development of enterprise-grade AI solutions including LLM-based systems, Retrieval-Augmented Generation (RAG), predictive ML models, decision intelligence platforms, and data-heavy applications
• Drive the full AI product lifecycle - opportunity discovery, business case definition, architecture design, development, deployment, monitoring, optimization and value realization
• Establish enterprise AI reference architectures, reusable frameworks, modular ML templates and standardized deployment patterns
• Ensure strong MLOps maturity including CI/CD for ML, model registry, automated retraining pipelines, monitoring for data/model drift, observability and governance
• Lead cloud-native AI platform strategy leveraging Azure / Databricks / AWS / GCP ecosystems with focus on scalability, resiliency and cost efficiency
• Define GenAI standards including prompt engineering frameworks, evaluation pipelines, guardrails, responsible AI controls and security compliance
• Partner with business leaders to translate complex operational challenges into scalable AI and data products with measurable ROI
• Define and track product KPIs including adoption, performance, latency, uptime, cost per inference, business value creation and productivity uplift
• Ensure enterprise-grade security, compliance, and responsible AI practices across all deployed solutions
• Drive continuous innovation by evaluating emerging AI technologies and integrating them into the enterprise ecosystem where strategically relevant
• Act as the single point of accountability for AI & Data product performance, delivery excellence and long-term platform scalability

YOUR TALENT

• University degree (B.Tech / M.Tech / M.S.) in Computer Science, Engineering or related discipline; MBA or equivalent business exposure is a plus
• 12+ years of experience across AI/ML, Data Platforms, or Enterprise Product Engineering, with 5+ years leading cross-functional technical teams
• Proven track record of building and scaling enterprise AI/ML products in production environments
• Deep understanding of:

  • Machine Learning lifecycle and model governance

  • LLMs, transformer architectures, RAG pipelines and prompt engineering strategies

  • MLOps frameworks including model monitoring, drift detection, retraining and CI/CD for ML

  • Modern data architectures (Databricks, Spark, ETL/ELT, Delta patterns, data orchestration)

  • API-driven architectures and distributed systems design

• Strong exposure to cloud ecosystems (Azure, Databricks, AWS or GCP) and cost optimization strategies for large-scale AI workloads
• Experience designing scalable, secure and highly available enterprise data platforms
• Strong strategic thinking with ability to align AI investments to business value, operational efficiency and competitive advantage
• Demonstrated experience influencing senior stakeholders and translating technical trade-offs into business decisions
• Strong leadership and talent development capability, with experience building engineering culture and technical maturity
• Excellent communication skills with ability to operate across business and technical audiences
• Hands-on mindset with ability to dive deep into architecture discussions when required
• Ability to operate in a fast-paced, high-growth and transformation-driven environment
• Fluent in Business English