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Senior Manager

EXL
Noida, IndiaPosted Aug 7, 2026
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  • Business Analysis of As-Is to Reimagined Workflows 

  • Design Solution Features & Functionalities 

  • Solution Lifecycle Management: Discovery-Prototype-Production Delivery-Enhancements-Scaling-DevSecOps 

  • Operations & Functional Stakeholders’ Interfacing

  • Accountability of Business Case definition, metrics, targets and realisation 

  • Solution Packaging, Business & Client’s Showcasing

Aligned to the Forward Deployment Engineering (FDE), who is a hands-on, stakeholder-facing who operates at the intersection of engineering, product, and delivery – embedding directly with functional teams to re-imagine, discover, and design AI solutions for production environments

Job Description

 

Position Title, Responsibility Level

AI Solutions Leads

 

 

Function

Enterprise AI

Reports to

VP / SVP – Enterprise AI

Permanent/ Temporary

Permanent

Experience

6-10 Years

Location

NCR/Bengaluru/Hyderabad

 

Role Summary (Strategic Mandate)

 

  • Business Analysis of As-Is to Reimagined Workflows 

  • Design Solution Features & Functionalities 

  • Solution Lifecycle Management: Discovery-Prototype-Production Delivery-Enhancements-Scaling-DevSecOps 

  • Operations & Functional Stakeholders’ Interfacing

  • Accountability of Business Case definition, metrics, targets and realisation 

  • Solution Packaging, Business & Client’s Showcasing

  • Aligned to the Forward Deployment Engineering (FDE), who is a hands-on, stakeholder-facing who operates at the intersection of engineering, product, and delivery – embedding directly with functional teams to re-imagine, discover, and design AI solutions for production environments

 

Key Responsibilities

1. AI-First Solution Engineering

  • Work with stakeholders’ and EXL delivery teams to deeply understand business workflows, data landscapes, and systems, and translate business problems into technical AI solution designs.

  • Rapidly build AI prototypes, POCs, and pilots, and take them through to production deployment and enterprise adoption.

  • Configure, customize, and extend EXL’s AI platforms and accelerators to fit business-specific contexts and constraints.

2. Agentic AI & AI Solution Development

  • Design and build agentic workflows, advances RAG pipelines, LLM integrations, tool-using agents, and human-in-the-loop systems.

  • Apply prompt engineering, evaluation frameworks, and fine-tuning techniques to achieve accuracy, reliability, and safety targets.

  • Integrate AI solutions with enterprise systems (APIs, data platforms, CRMs, contact center and core operations systems).

3. Deployment, Integration & Production Ownership

  • Own end-to-end deployment: environment setup, CI/CD, LLMOps/MLOps, monitoring, guardrails, and observability.

  • Ensure solutions are secure, compliant, and production-grade, aligned with responsible AI, privacy, and EXL security standards.

  • Troubleshoot live systems and continuously optimize for latency, cost, quality, and scale.

4. Stakeholder Engagement & Value Realization

  • Act as a trusted technical advisor to stakeholders; lead demos, workshops, and technical deep dives.

  • Define success metrics and demonstrate measurable outcomes: productivity gains, cost reduction, risk mitigation, and revenue uplift.

  • Capture field feedback and channel it into EXL’s platform and product roadmaps.

5. Collaboration & Knowledge Sharing

  • Collaborate closely with platform engineering, data science, and delivery teams across geographies.

  • Create reusable assets, accelerators, playbooks, and documentation from multiple deployments.

  • Mentor engineers and evangelize best practices in applied and agentic AI across accounts.

Technical & Architecture Expertise (Agentic AI)

  • Strong hands-on software engineering skills (Python and/or TypeScript), including APIs, microservices, and cloud-native development on AWS, Azure, or GCP.

  • Practical experience building with agentic AI frameworks such as LangGraph, LangChain, CrewAI and emerging standards like MCP (Model Context Protocol).

  • Deep working knowledge of foundation models and platforms, including OpenAI, Anthropic Claude, and open-source LLM stacks; strong grasp of RAG, embeddings, and vector databases.

  • Experience with LLMOps/MLOps: evaluation, monitoring, guardrails, versioning, and cost/performance optimization in production.

  • Exposure to multimodal AI technologies (voice, avatar, video) using platforms like ElevenLabs and HeyGen.

  • Fluency with AI-native developer tools such as Cursor, Replit, Claude Code, and related copilots.

  • Ability to design solutions within enterprise-grade architecture, security, and responsible AI guardrails, balancing scalability, cost, and compliance.

 

Key Outcomes & Success Metrics

  • High POC-to-production conversion and rapid deployment velocity across engagements.

  • Tangible business outcomes – productivity, cost, quality, and revenue impact – attributable to deployed solutions.

  • Reusable solution assets and accelerators adopted across multiple accounts, not one-off builds.

  • Strong production reliability, security, and responsible AI compliance posture for deployed solutions.

  • High satisfaction and expansion of EXL’s AI footprint within assigned accounts.

 

Required Experience & Qualifications

  • 4–8 years of experience in software engineering, applied AI/ML, or solution engineering, with 2+ years of hands-on GenAI/LLM development.

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience).

  • Proven track record of:

    • Shipping production GenAI/agentic AI solutions for enterprise functions

    • Working directly with business stakeholders in consulting, forward-deployed, or solution engineering roles

    • Delivering measurable business outcomes from AI deployments

  • Strong understanding of:

    • Agentic AI and LLM architectures, RAG, and evaluation

    • Data platforms, cloud, security, and compliance

    • Enterprise integration and legacy system modernization

  • Willingness to travel and work onsite at business locations as required.

 

Leadership & Behavioral Expectations

  • Owner’s mindset with a strong bias for action and outcome orientation.

  • Comfort with ambiguity, rapid iteration, and fast-changing environments.

  • Exceptional communication skills – able to translate deep technical work into business value for executives.

  • Collaborative, and AI-first working style across diverse teams.

  • Deep commitment to responsible AI and ethical deployment.

  

Why This Role Matters to EXL

  • Forward Deployment Engineers are the bridge between EXL’s AI platforms and real value – proving AI works in production, not just in demos.

  • This role directly shapes how EXL builds, deploys, and scales AI, accelerating the journey to an AI-native enterprise partner.

  

 

 

 

 

Bachelor of Masters degree in Computer Science, Finance, Human Resources, Business Management Certification in Oracle Fusion (ERP, PPM, EPM, HCM, SCM), Salesforce (Sales CRM, CPQ), Microsoft (Azure, Power BI, Sharepoint), ServiceNow other relevant Core Systems. Project Management, Digital Transformation Min 10 years

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