NIIT

Key Responsibilities

1. Solutioning & Proposal Development

•   Partner with Senior SMEs and Practice Leads to design end-to-end Data & AI solutions for client pursuits — contributing to structure, content, and commercial framing.

•   Build client proposals, solution documents, and program structures that are well-organized, accurate, and ready to use without significant rework.

•   Translate client requirements into structured, outcome-oriented learning journeys — adoption, capability uplift, and measurable business outcomes, not just module lists.

•   Support customized offerings across Data Engineering, AI / ML, and GenAI and Agentic AI tracks; help assemble pursuits from existing accelerators rather than rebuilding from scratch.

2. Client Engagement Support

•   Participate in client discussions, discovery calls, and requirement-gathering sessions — capture context with the rigour that makes the next conversation sharper.

•   Convert business needs into solution frameworks and delivery models with guidance from Senior SMEs; document customer priorities so Practice and Sales can act on them.

•   Support pitch decks, case studies, and success stories — buyer-specific, visually clean, and aligned to how the customer thinks about their own problem.

•   Stay engaged through the proposal cycle and handoff to delivery; ensure no requirement gets lost between discovery and execution.

3. Content & Program Structuring

•   Assist in designing curriculum outlines, learning journeys, and hands-on lab structures that hold up against real-world enterprise contexts.

•   Work with internal and external SMEs to ensure content aligns with current industry trends, real use cases, and business outcomes — not generic technology overviews.

•   Maintain a library of reusable program structures, slide assets, and case study inserts; flag gaps in the existing content library proactively.

4. Research & Market Intelligence

•   Track trends across the AI / GenAI / LLM ecosystem and Data Engineering & Analytics — translate findings into usable inputs for outreach, pitching, and offering design.

•   Identify new solution opportunities and product ideas based on market signals, customer asks, and competitor moves.

•   Benchmark StackRoute's offerings against competitors; surface gaps and differentiation angles for Senior SMEs and Practice Leads to act on.

5. Internal Collaboration

•   Work fluidly with Delivery, Sales, and external SMEs to ensure solutions designed on paper actually work in delivery — surface feasibility risks early, not late.

•   Coordinate inputs across Practice teams during pursuit cycles; hand off to delivery with documentation that captures customer commitments and success metrics.

Must Have Technical & Functional Skills

•   Good understanding of terminologies in Data Engineering (ETL, pipelines, data lakes), Data Analytics & BI concepts, and Machine Learning fundamentals, AI tools ( not technical expertise but L1-L2 knowledge should be present from application standpoint).

•   Awareness of GenAI / LLM vocabulary — prompt engineering, RAG, APIs — with enough depth to hold a credible first conversation with a technical stakeholder.

•   Strong PowerPoint skills (client-ready decks), Excel for effort estimation and costing basics, and structured documentation — proposals, SoWs, one-pagers.

•   Strong problem-solving and structured thinking — breaks complex requirements into clear, communicable solutions.

•   Comfortable communicating with both technical and non-technical stakeholders; good storytelling and presentation instincts; understanding of L&D context is a plus.

Qualifications & Experience

Required:

•   5-15 years in the education products, or in solutioning, pre-sales, or consulting roles with exposure of 3-5 years in Data/AI/Analytics.

•   Bachelor's or Master's in Computer Science, Data Science, Engineering, or a related discipline.

Nice to Have competences:

•   Prior pre-sales, proposal writing, or design development experience.

•   Certifications in cloud, data, or AI platforms (AWS, Azure, GCP, or model-provider certifications).

Core Competencies

·      Structured Thinking: Organises ambiguous client and technical inputs into logical, buyer-relevant narratives. Builds proposals that flow from problem to solution.

·      Solution Articulation: Translates Data & AI capabilities into crisp, persona-specific stories. Adapts the pitch for a CTO, L&D Head, or BU Head without losing substance.

·      Research & Synthesis: Gathers and distils large volumes of information into sharp, usable outputs. Knows what to include and what to leave out.

·      Written Communication: Writes a tight brief, a clean slide, and a clear email. Adapts register from internal working notes to buyer-facing collateral.

·      Curiosity & Learning Agility: Picks up new tools, concepts, and sectors quickly. Tracks AI / GenAI shifts proactively rather than waiting to be told what to read.

·      Bias for Action: Ships a useful 10-slide deck on time rather than a polished 20-slide deck that's late. Comfortable with iteration over perfection.

Key Responsibilities

1. Performance Management & PMS Excellence

• Drive end-to-end execution of the annual PMS cycle including goal setting, mid-year reviews, year-end assessments, calibration, moderation, and communication.

• Manage PMS governance calendar, dashboards, compliance tracking, and stakeholder coordination across IBUs.

• Support calibration forums by preparing insights, analytics, and ensuring consistency of performance outcomes.

• Partner on PMS process improvements, technology enhancements, workflow optimisation, and reporting requirements.

• Build performance insights to support talent, rewards, and workforce decisions.

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2. Talent Reviews & Succession Planning

• Execute annual talent review and 9-box processes in partnership with Business Leaders and HRBPs.

• Support identification and segmentation of critical talent, HiPos, emerging leaders, and talent pools.

• Maintain talent dashboards and heat maps highlighting capability strength, readiness, and talent risks.

• Support succession planning for critical roles through readiness assessment, successor identification, and development actions.

• Enable integration between performance outcomes, talent reviews, succession, and internal mobility.

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3. Leadership Development & Talent Programmes

• Support design and execution of leadership development journeys across manager, mid-level, and leadership populations.

• Coordinate flagship talent programmes, mentoring, coaching, and development interventions.

• Track programme effectiveness through participation, capability improvement, movement, retention, and business impact metrics.

• Support IDP frameworks and development planning for HiPo and critical talent segments.

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4. Culture & Organisational Health

• Support culture initiatives through employee listening insights, engagement data, GPTW inputs, and organisational health metrics.

• Drive execution of culture activation initiatives including manager connects, leadership engagements, and employee experience interventions.

• Support employer recognition programmes including GPTW and workplace benchmarking submissions.

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5. Talent Analytics & Reporting

• Develop and maintain talent dashboards covering:

o Talent pipeline

o Succession readiness

o HiPo movement

o Performance insights

o Attrition trends

o Leadership capability indicators

• Provide periodic talent insights and recommendations to enable leadership decision-making.

• Partner with HR Technology teams on talent systems, data accuracy, and reporting improvements.

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Key Stakeholders

Internal:

Head – Talent Management COE | HRBPs | Business Leaders | L&D | C&B | HR Technology | Corporate Communications

External:

Leadership development partners | Assessment providers | Talent advisory firms | Employer recognition platforms

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Qualifications & Experience

• MBA / PGDM in Human Resources from a reputed institution.

• 10– 14 years of HR experience with strong exposure to Talent Management, Performance Management, OD, or HR COE roles.

• Experience in executing enterprise talent processes including PMS, talent reviews, succession planning, and leadership development.

• Understanding of talent frameworks, assessment methodologies, and people analytics.

• Exposure to HR technology platforms (SAP SuccessFactors / Workday / equivalent) preferred.

• Strong stakeholder management, execution discipline, analytical orientation, and ability to work with senior leaders.