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Delivery Lead - AI Engineer
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Job Info
- Job Identification16464
- Posting Date07/13/2026, 07:44 AM
- Job RoleProject Management-Delivery Lead
- Experience (In Years)12-15
- Job LocationPune
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.
Responsibilities
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.
Qualifications
- 12+ years of overall experience in AI engineering, data engineering, cloud technologies, data platforms, or enterprise technology delivery.
Required Skills
- Attention To Consistency
- CI/CD Automation
- Data Engineering Management
- Data Engineering Strategy
- Data Security
- DevOps Practices
- Internal Communications
- Interpersonal Relationship Building
- Leadership Capabilities
- Optimization Tool
- Working under Pressure
About Us
EXL (NASDAQ: EXLS) is a leading data analytics and digital operations and solutions company. We partner with clients using a data and AI-led approach to reinvent business models, drive better business outcomes and unlock growth with speed. EXL harnesses the power of data, analytics, AI, and deep industry knowledge to transform operations for the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect. We are headquartered in New York and have more than 54,000 employees spanning six continents. For more information, visit www.exlservice.com.
EXL never requires or asks for fees/payments or credit card or bank details during any phase of the recruitment or hiring process and has not authorized any agencies or partners to collect any fee or payment from prospective candidates. EXL will only extend a job offer after a candidate has gone through a formal interview process with members of EXL’s Human Resources team, as well as our hiring managers.
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