Delivery Lead - AI Engineer

EXL Talent Acquisition Team; Pune District; On-site; INR 3,500,000 - 6,500,000; Full time

Job summary

EXL Talent Acquisition Team is seeking an experienced Delivery Lead – AI Engineer in Pune, India. The role demands a 12+ year track record delivering AI, data engineering, and cloud-based programs for Banking/Financial Services.

You will lead end-to-end implementations, engage with clients, and guide cross-functional teams to achieve scalable, compliant solutions. The candidate should excel in governance, risk management, stakeholder reporting, and technical leadership, ensuring delivery

Qualifications

• 12+ years of experience in AI engineering, data engineering, cloud technologies, data platforms, or enterprise technology delivery.
• Strong experience leading AI engagements, client-facing delivery programs, and cross-functional engineering teams.
• Hands-on understanding of AI/ML concepts, GenAI solutions, automation use cases, model integration, and AI-enabled engineering practices.
• Strong knowledge of Databricks, Snowflake, Data Lakes, Data Warehouses, and Lakehouse architectures.
• Experience with AWS, Azure, or GCP.
• Strong Python, SQL, Spark, PySpark, ETL/ELT pipelines, orchestration, and large-scale data processing.
• Experience in delivery governance, risk management, stakeholder reporting, estimation, planning, and quality assurance.
• Excellent communication, leadership, problem-solving, stakeholder management, and client engagement skills.

Responsibilities

• Lead end-to-end delivery of AI, data engineering, and cloud-based transformation engagements.
• Drive client engagement by understanding business priorities, managing expectations, and presenting solutions.
• Provide technical and delivery leadership across AI/ML, GenAI, data platforms, cloud, and enterprise architecture initiatives.
• Own delivery planning, execution tracking, governance, quality, and stakeholder reporting for complex programs.
• Collaborate with stakeholders to define solution roadmaps and execution plans.
• Guide teams in designing scalable, secure, and cost-effective AI/data solutions.
• Mentor and develop engineering teams to ensure delivery excellence.
• Promote best practices across AI engineering, data engineering, DevOps, and compliance.

Skills

AI engineering

Data engineering

Cloud technologies

Delivery governance

Stakeholder management

Client engagement

Python

SQL

Spark

GenAI

Tools

Databricks

Snowflake

Data Lakes

Data Warehouses

Lakehouse architectures

AWS

Azure

GCP

ETL/ELT pipelines

Orchestration

Job description

Job Description: Delivery Lead – AI Engineer

Experience: 12+ years

Role Summary

We are looking for an experienced Delivery Lead – AI Engineer with strong expertise in AI-led solution delivery, data engineering, cloud platforms, and enterprise-scale technology programs. The ideal candidate should have proven experience in Banking, Capital Markets, or Financial Services and the ability to lead AI engagements, manage client stakeholders, drive delivery governance, and ensure successful execution of complex technology initiatives.

Key Responsibilities

• Lead end-to-end delivery of AI, data engineering, and cloud-based transformation engagements.
• Drive client engagement by understanding business priorities, managing expectations, presenting solutions, and ensuring timely resolution of risks and issues.
• Provide technical and delivery leadership across AI/ML, GenAI, data platforms, cloud, and enterprise architecture initiatives.
• Own delivery planning, execution tracking, governance, quality, and stakeholder reporting for complex programs.
• Collaborate with business stakeholders, architects, product owners, engineering teams, and leadership to define solution roadmaps and execution plans.
• Guide teams in designing scalable, secure, and cost-effective AI and data solutions aligned with enterprise standards.
• Mentor, manage, and develop engineering teams to ensure delivery excellence and continuous capability improvement.
• Promote best practices across AI engineering, data engineering, DevOps, automation, performance optimization, and compliance.

Required Skills

• 12+ years of overall experience in AI engineering, data engineering, cloud technologies, data platforms, or enterprise technology delivery.
• Strong experience leading AI engagements, client-facing delivery programs, and cross-functional engineering teams.
• Hands-on understanding of AI/ML concepts, GenAI solutions, automation use cases, model integration, and AI-enabled engineering practices.
• Strong knowledge of modern data platforms such as Databricks, Snowflake, Data Lakes, Data Warehouses, and Lakehouse architectures.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Strong understanding of Python, SQL, Spark, PySpark, ETL/ELT pipelines, orchestration, and large-scale data processing.
• Experience in delivery governance, risk management, stakeholder reporting, estimation, planning, and quality assurance.
• Excellent communication, leadership, problem-solving, stakeholder management, and client engagement skills.

Domain Experience

Must have strong experience in Banking, Capital Markets, or Financial Services, with exposure to regulatory, risk, compliance, data governance, and enterprise technology environments.

Preferred Skills

• Experience delivering AI, GenAI, or intelligent automation solutions in enterprise environments.
• Exposure to data governance, metadata management, data cataloging, security controls, and compliance frameworks.
• Experience supporting solution reviews, technical assessments, hiring, and capability-building initiatives.
• Ability to translate business problems into practical AI and data-driven solutions.

Key Attributes

• Strong delivery ownership with a client-first mindset.
• Ability to lead complex AI and data programs with clarity, accountability, and execution discipline.
• Excellent stakeholder management and executive communication skills.
• Strategic thinker with a hands-on technical approach.
• Ability to build high-performing teams and drive continuous improvement.