{"id":3046690,"url":"https://alion.io/job/exl-delivery-lead-ai-engineer","title":"Delivery Lead - AI Engineer","company":{"id":38016,"name":"EXL","domain":"exlservice.com","url":"https://alion.io/company/exl","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":80,"open_postings":261,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":15,"computed_at":"2026-10-27T05:46:45Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":22000,"max_usd":57000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":47},"experience_years_min":12,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-08-20T16:39:28Z","employer_posted_date":"2026-08-20","last_verified_at":"2026-10-27T15:07:51Z","board_verified":true,"closed_at":null,"days_open":68,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":68},"description":"Job Description: Delivery Lead - AI Engineer\nExperience: 12+ years\nRole Summary\nWe 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.\nKey Responsibilities\nLead end-to-end delivery of AI, data engineering, and cloud-based transformation engagements.\nDrive client engagement by understanding business priorities, managing expectations, presenting solutions, and ensuring timely resolution of risks and issues.\nProvide technical and delivery leadership across AI/ML, GenAI, data platforms, cloud, and enterprise architecture initiatives.\nOwn delivery planning, execution tracking, governance, quality, and stakeholder reporting for complex programs.\nCollaborate with business stakeholders, architects, product owners, engineering teams, and leadership to define solution roadmaps and execution plans.\nGuide teams in designing scalable, secure, and cost-effective AI and data solutions aligned with enterprise standards.\nMentor, manage, and develop engineering teams to ensure delivery excellence and continuous capability improvement.\nPromote best practices across AI engineering, data engineering, DevOps, automation, performance optimization, and compliance.\nRequired Skills\n12+ years of overall experience in AI engineering, data engineering, cloud technologies, data platforms, or enterprise technology delivery.\nStrong experience leading AI engagements, client-facing delivery programs, and cross-functional engineering teams.\nHands-on understanding of AI/ML concepts, GenAI solutions, automation use cases, model integration, and AI-enabled engineering practices.\nStrong knowledge of modern data platforms such as Databricks, Snowflake, Data Lakes, Data Warehouses, and Lakehouse architectures.\nExperience with cloud platforms such as AWS, Azure, or GCP.\nStrong understanding of Python, SQL, Spark, PySpark, ETL/ELT pipelines, orchestration, and large-scale data processing.\nExperience in delivery governance, risk management, stakeholder reporting, estimation, planning, and quality assurance.\nExcellent communication, leadership, problem-solving, stakeholder management, and client engagement skills.\nDomain Experience\nMust have strong experience in Banking, Capital Markets, or Financial Services, with exposure to regulatory, risk, compliance, data governance, and enterprise technology environments.\nPreferred Skills\nExperience delivering AI, GenAI, or intelligent automation solutions in enterprise environments.\nExposure to data governance, metadata management, data cataloging, security controls, and compliance frameworks.\nExperience supporting solution reviews, technical assessments, hiring, and capability-building initiatives.\nAbility to translate business problems into practical AI and data-driven solutions.\nKey Attributes\nStrong delivery ownership with a client-first mindset.\nAbility to lead complex AI and data programs with clarity, accountability, and execution discipline.\nExcellent stakeholder management and executive communication skills.\nStrategic thinker with a hands-on technical approach.\nAbility to build high-performing teams and drive continuous improvement.\n Key Responsibilities\nLead end-to-end delivery of AI, data engineering, and cloud-based transformation engagements.\nDrive client engagement by understanding business priorities, managing expectations, presenting solutions, and ensuring timely resolution of risks and issues.\nProvide technical and delivery leadership across AI/ML, GenAI, data platforms, cloud, and enterprise architecture initiatives.\nOwn delivery planning, execution tracking, governance, quality, and stakeholder reporting for complex programs.\nCollaborate with business stakeholders, architects, product owners, engineering teams, and leadership to define solution roadmaps and execution plans.\nGuide teams in designing scalable, secure, and cost-effective AI and data solutions aligned with enterprise standards.\nMentor, manage, and develop engineering teams to ensure delivery excellence and continuous capability improvement.\nPromote best practices across AI engineering, data engineering, DevOps, automation, performance optimization, and compliance.\n 12+ years of overall experience in AI engineering, data engineering, cloud technologies, data platforms, or enterprise technology delivery.","description_format":"text","description_chars":4658,"description_truncated":false,"requirements":{"experience_years_min":12,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Business Process Outsourcing (BPO)","AI Consulting & Integration","Analytics & BI 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