Senior Manager, Technology Consulting, Applied AI

EPAM's Applied AI group helps our business units and their clients turn AI opportunities into solutions that are technically credible and ready to deliver. As a Senior Manager, Technology Consulting , you will be a trusted technical advisor on client pursuits and a key contributor to integrated solution shaping. You will work with Growth Leads, client partners and Principals to help qualify opportunities, connect business needs with technical capabilities, and bring together specialists from across EPAM practices to shape cohesive solutions. You will advise business and technology stakeholders and show how agentic AI and GenAI can transform business processes, including through quick, clickable prototypes. You will partner with Applied AI colleagues, Forward Deployed AI Architects, product management, Engineering and delivery teams to make technical trade-offs, risks and costs explicit before a client commits. This role focuses on technical strategy, pre-sales and integrated solution shaping, and complements our Forward Deployed AI Architects, who concentrate on client-embedded architecture and technical implementation. Senior Managers may stay involved selectively during early delivery to ensure a smooth transition, but long-term implementation is not the primary focus, and the role does not carry account ownership. You will work across a portfolio of clients at once, from short pre-sales pursuits to consulting engagements lasting a couple of months. Req.# Responsibilities Support technical qualification and AI pre-sales, partnering with Growth Leads, client partners and Principals to define business outcomes, connect them to technical capabilities and shape technically credible solution propositions Contribute to integrated solution shaping across EPAM practices, working with specialist teams to develop cohesive, delivery-ready solutions and supporting pursuits from first conversation through commitment Engage and advise client stakeholders, building trust through clear solution narratives and credible technical judgment Advise on agentic AI, RAG, automation, model and platform choices, and build-versus-buy options, making trade-offs explicit through vendor evaluation across a vendor-neutral landscape (OpenAI, Anthropic, AWS, Microsoft, Google) Turn ideas into evidence quickly by building or directing clickable prototypes with clients to demonstrate value Contribute to AI readiness assessments across business processes, data, platforms, integration and security, using maturity models where they help Help define enterprise AI foundation requirements for identity, models, agents, knowledge, AI governance, evaluation and AI observability as solutions scale Develop architecture options and pre-sales proposal content, working with Growth Leads and Applied AI Leads to turn shaped solutions into compelling client propositions Review design and proof evidence from architects and engineers, and contribute to documented technical readiness recommendations Collaborate across EPAM practices (Data, Intelligent Automation, hyperscaler and AI partner teams) to build win-win propositions for clients Help align scope, risks and estimates with the delivery organization before commitment, support delivery-ready solutions and a clear, accepted technical handoff, with selective involvement in early delivery as needed Contribute to reusable technical playbooks and solution packs, and mentor consultants and client-facing teams Requirements Software engineering or solution architecture foundation with real hands-on experience, so you can speak credibly with architects and engineers and, where needed, build as well as advise Experience in client-facing technology consulting or AI pre-sales: partnering with clients to define outcomes, qualify opportunities and shape AI solutions Hands-on experience building with GenAI and agentic AI, including LLM selection, capabilities and limitations, enterprise adoption, and evaluation of quality and safety Working knowledge of common GenAI solution patterns such as retrieval-augmented generation (RAG) and agentic workflows, including orchestration, autonomy boundaries and human-in-the-loop design. Deep production experience with any specific pattern or framework is not required Depth in one or two primary technology stacks (for example Anthropic, OpenAI, AWS or Azure), with the breadth of a strong technical generalist and a technology-agnostic approach Ability to quickly turn around a clickable prototype with a client. Production-grade delivery is not expected Strong written and verbal communication in ambiguous client settings: solution narratives, technical proposals, architecture recommendations and executive presentations Experience supporting complex technical pursuits, coordinating specialist teams, mentoring consultants and engaging client stakeholders Collaboration skills to partner effectively across practices and with technology partners Nice to have Deeper expertise in a specific industry domain. Generalists are welcome Exposure to AI governance, responsible AI, compliance assurance, risk management, privacy and model oversight Experience conducting AI maturity assessments and applying enterprise maturity models Experience leading vendor evaluation and technology selection, including platform assessments and proof-of-concept reviews Familiarity with enterprise architecture topics such as Identity and Access Management, security, APIs, event-driven architectures and integration patterns Knowledge of AI observability, AI data governance (quality, lineage, stewardship) and AI platform lifecycle management Understanding of agentic operating model transformation: the organizational, process and governance changes needed to scale AI-enabled ways of working Experience with solution estimation, cost modeling and Cloud FinOps principles