Infosys Consulting is looking for a seasoned AI Consulting Specialist with strong commercial instincts and broad technical awareness across the AI landscape. This is a consulting role — the individual will advise clients, shape AI strategies, articulate AI solution approaches, and actively participate in pseudo-sales and offering development. They are expected to be technically conversant enough to engage credibly with client engineers, AI architects, and C-suite leaders — including Chief AI Officers (CAIO) and Chief Data Officers (CDO) — without being a hands-on developer.
Responsibilities:
Key responsibilities include:
- AI Advisory & Solution Shaping: Advise clients on AI strategy, solution landscape, and approach — translating complex business problems into clear AI solution narratives without necessarily designing the architecture in depth
- Pseudo-Sales & Pre-Sales: Lead and actively participate in RFP responses, client workshops, discovery calls, PoC scoping, and solution pitches; support account teams in shaping and closing AI consulting deals.
- C-Suite Engagement: Engage directly with Chief AI Officers (CAIO), Chief Data Officers (CDO), CTOs, and senior business leaders to articulate AI value, strategy, and roadmap; hold credible technical conversations at the executive level.
- Agentic AI Awareness: Understand how Agentic AI and multi-agent systems work (LangGraph, AutoGen, CrewAI, Semantic Kernel, LlamaIndex) well enough to advise clients, scope engagements, and validate delivery team approaches — without hands-on building.
- AI Offerings Development: Co-create and articulate go-to-market AI consulting offerings, point-of view documents, and solution accelerator narratives for the practice.
- Domain Fluency: Apply AI thinking to specific industry contexts (Life Sciences, Pharma, BFSI, Supply Chain, etc.) — framing use cases, business value, and implementation considerations for client conversations.
- AI Governance & Regulatory Advisory: Advise clients on EU AI Act, responsible AI principles, model risk management, and AI compliance — particularly in regulated industries.
- Thought Leadership: Contribute to white papers, POV documents, conference presentations, and internal community building.
- Team Guidance: Provide consulting direction and oversight to delivery teams; review and validate AI solution designs without personally building them.
- Billability & Practice Growth: Expected to maintain 65%–75% billability annually through active client engagements, while dedicating the remaining time to practice development activities — including offering creation, RFP pursuit, thought leadership, and capability building.
Mandatory Skills (candidates without these need not apply):
- AI Technical Awareness - Broad understanding of AI solution landscape — ML, LLMs, Generative AI, Agentic AI, RAG — sufficient to lead client conversations, validate approaches, and scope engagements; not required to build or code.
- Agentic AI Conceptual Fluency: Ability to explain, position, and advise on multi-agent AI systems and frameworks (LangGraph, AutoGen, CrewAI, Semantic Kernel, LlamaIndex); awareness of patterns, limitations, and use case fit
- LLM & Generative AI Literacy: Strong conceptual knowledge of LLMs, RAG, prompt engineering, fine-tuning, and model evaluation — able to hold technical conversations with client AI teams and challenge/validate delivery approaches
- AI Frameworks & Cloud Platforms: Awareness of major AI platforms and frameworks (Azure OpenAI, AWS Bedrock, Google Vertex AI, Hugging Face, LangChain) — can discuss trade-offs and platform selection with clients without being a platform engineer
- Pre-Sales / Pseudo Sales: Minimum 3 years of active AI-focused pre-sales / pseudo-sales experience: RFP/RFI responses, solution shaping, client pitches, and deal pursuit in AI or data consulting
- AI Governance & Regulatory Knowledge: Working knowledge of EU AI Act, responsible AI principles, model risk management, and AI compliance frameworks; able to advise clients on AI governance strategy
- C-Suite Stakeholder Engagement: Demonstrated experience engaging directly with Chief AI Officers (CAIO), Chief Data Officers (CDO), CTOs, or equivalent senior client executives; comfortable leading executive-level AI advisory conversations
- Domain Expertise: Strong understanding of at least one industry vertical (Life Sciences, Pharma, BFSI, Manufacturing, etc.); ability to contextualize AI use cases and value propositions for that domain
- Consulting Background & Experience: 14+ years total experience, with the majority in consulting roles at a Tier 1 IT company (Infosys, TCS, Wipro, Cognizant, Accenture, Capgemini) or Big 4 / management consulting firm (Deloitte, EY, KPMG, PwC, McKinsey, BCG); at least 3 years in AI-specific consulting or advisory
- Communication & Storytelling: Exceptional ability to craft and deliver compelling narratives — proposals, executive briefings, POVs, and offering decks — that translate technical AI concepts into business value for senior audiences
Basic Qualifications:
Demonstrates proven success in roles and thorough abilities in one or more of the following areas:
- Education: Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, Engineering, Business, or related field
- Total Experience:14+ years, with at least 3 years in AI consulting, AI advisory, or AI-led presales roles
- Previous Employers: Infosys, TCS, Wipro, Cognizant, Accenture, Capgemini, HCL Tech, IBM, Deloitte, EY, KPMG, PwC, McKinsey & Company, BCG, or equivalent Tier 1 / Big 4 / consulting organizations
Desirable Skills:
- MLOps & AI Engineering Awareness: Familiarity with MLOps concepts (MLflow, Kubeflow, CI/CD for AI) — enough to scope, advise, and oversee; not hands-on implementation
- Vector Databases & Semantic Search: Awareness of vector databases (Pinecone, Weaviate, pgvector, Azure AI Search) and their role in RAG architectures; able to advise clients on selection and use cases
- AI Offering / Accelerator Development: Experience in packaging AI consulting capabilities as reusable offerings, solution accelerators, or practice assets for BD purposes
- Regulatory Domain AI: Familiarity with FDA 21 CFR Part 11, GxP AI validation, or equivalent — able to advise clients in regulated industries on AI compliance
- Knowledge Graphs & Ontologies: Conceptual awareness of knowledge graph-based AI augmentation; able to discuss applicability with client data and AI teams
- AI Ethics & Responsible AI: Understanding of AI bias, fairness, explainability, and responsible AI governance frameworks — able to advise clients and shape responsible AI policies
- Proposal / BD Leadership: Led or co-led AI consulting proposals exceeding $2M in TCV
- Certifications: AWS Certified ML Specialty, Google Professional ML Engineer, Azure AI Engineer Associate, or equivalent
- Thought Leadership: Published articles, conference talks, or contributed to AI policy / strategy forums
- Data Strategy Awareness: Understanding of data strategy, data mesh, and data platform concepts as the foundation for enterprise AI
