AI Architect

Experience: 12years Location: Hyderabad/Bangalore Notice period : Immediate to 60days The Role We are hiring an Architect, AI, Data Science & Data Engineering to set the technical direction for one of our most strategic practices. This is a player-coach leadership role spanning engineering leadership, AI and data science, and data engineering. You will own the technical vision, the architecture, and the health of the teams that execute it .You will set technical direction across complex problems, grow and mentor a multidisciplinary team of engineers and architects, and stay close enough to the technology to earn the trust of the people you lead What You'll Own Engineering leadership Set the technical vision and architecture for the practice's hardest, most novel problems Operate as a hands-on technical authority in design reviews and the deepest architectural decisions Define modern, cloud-native and AI-native reference architectures that the team can build on AI / ML & Data Lead the practice's generative, agentic, and ML capabilities — from data foundations through modeling and evaluation Architect AI-ready data platforms: cloud-native pipelines, lineage and observability, governance, and metadata management at enterprise scale Establish responsible-AI and evaluation practices so solutions are reliable, measurable, and trustworthy R&D & exploring new ideas Drive an active R&D agenda — exploring emerging AI techniques, tools, and architectures ahead of the market Prototype complex, ambitious ideas quickly to test feasibility and prove value Create space for the team to experiment, learn, and turn research into practical capability Customer & client conversations Engage directly with customers and clients as the senior technical voice — discovery, framing problems, and shaping what's possible Translate client needs into technical direction, and technical possibility into language executives understand Build trusted technical relationships that open new conversations, ideas, and opportunities People & practice Hire, mentor, and grow a multidisciplinary team of engineers, ML practitioners, and architects Be accountable for career growth, performance management, and a strong, inclusive engineering culture Define hiring plans, skills development, and a healthy bench aligned to demand What You Bring We care far more about demonstrated depth and breadth than years on a résumé. The right person is fluent across the full data science spectrum and knows which technique fits which problem Hands-on comfort across the full range of data science: tree-based methods, linear models, stochastic processes, computer vision, graph ML, NLP, agentic AI, reinforcement learning, and LLMs The judgment to select the right approach for each problem — and to justify the trade-offs to both engineers and executives Proven technical leadership in a consulting, professional services, or product engineering environment serving enterprise clients Hands-on depth in modern data engineering and cloud-native architecture: pipelines, DataOps, governance, and MLOps/LLMOps Comfort with Temporal for durable workflow orchestration — building reliable, long-running data, ML, and agentic pipelines Architecture-level fluency in at least one major cloud (AWS, GCP, or Azure) and the modern data/ML tooling ecosystem Track record of leading teams through ambiguous, research-heavy problems to working solutions Exceptional communicator who can move between a whiteboard with engineers and a boardroom with C-level stakeholders Successful clearance of the GAIA Interview as part of the selection process (required) Nice to Have Experience building or scaling an AI/ML or data engineering practice from the ground up Familiarity with production GenAI: RAG, agentic workflows, evaluation frameworks, and LLMOps Domain knowledge in a strategic vertical (retail, financial services, manufacturing, healthcare, or technology) A visible public thought-leadership presence: talks, publications, open-source, or reference architectures Experience managing distributed, multi-country engineering teams What We Offer The mandate to shape and scale a strategic, high-visibility AI and data practice Work with Fortune 1000 clients on transformative, AI-first problems with real business impact Strong leadership exposure, competitive compensation, and a culture that values engineering excellence and continuous learning A boutique-feel, global-scale environment with access to the latest in generative, agentic, and physical AI About Grid Dynamics Grid Dynamics (Nasdaq: GDYN) is an AI-first digital engineering and technology consulting company. Founded in Silicon Valley in 2006, we transform Fortune 1000 enterprises through advanced generative, agentic, and physical AI, modern data platforms, and cloud-native engineering. With roughly 5,000 technical professionals across 19 countries, we pair the personal attention of a boutique partner with the engineering muscle of a global powerhous e.Our Forward Deployed Engineers embed inside client teams to deliver measurable business outcomes — and our Grid Dynamics AI Native (GAIN) platforms accelerate enterprise AI transformation with security, scale, and ROI from day one.