Job description
Experience: 8+ Years
Own the end-to-end solutioning process - from understanding client requirements to designing architectures that are technically sound and commercially viable.
Partner with pre-sales and business development to respond to RFPs, build proposals, create solution decks, and lead client presentations and discovery calls.
Conduct architecture reviews and technical assessments for ongoing projects, ensuring solutions align with best practices, scalability, security, and client expectations.
Translate complex business problems into clear, structured technical solutions spanning AI, cloud, backend systems, and integrations.
Define high-level and low-level architecture for AI-native applications, including LLM integrations, RAG pipelines, agentic workflows, MCP-based tool/agent integrations, and enterprise data platforms.
Act as a technical advisor to clients during pre-sales and early delivery phases, building confidence and trust through clarity and expertise.
Collaborate with engineering teams to ensure smooth handoff from solutioning to execution, maintaining architecture integrity throughout delivery.
Evaluate build-vs-buy and model/provider trade-offs (LLMs, vector databases, orchestration frameworks) to recommend the right AI stack for each client's needs.
Stay current with emerging AI technologies, cloud platforms, and enterprise architecture trends to bring relevant, forward-thinking solutions to clients.
Strong foundation in backend engineering - Python, REST APIs, microservices, and distributed systems.
Hands-on experience with cloud platforms (AWS, Azure, or GCP), CI/CD, Docker, and Kubernetes.
Deep understanding of AI-native solution design - LLM integrations, RAG pipelines, AI agents and agentic workflows, MCP (Model Context Protocol), vector databases, prompt engineering, and multi-agent orchestration.
Familiarity with LLMOps practices - model evaluation, observability, cost/latency optimization, and responsible-AI/governance considerations.
Experience with enterprise databases, data architecture, and integration patterns.
Proven ability to create solution documents, architecture diagrams, and proposal decks that are clear and client-ready.
Strong grasp of security, scalability, and compliance considerations in enterprise systems.