4 months ago
Bengaluru, IndiaStaff+
Responsibilities
- Own solution architecture and technical delivery for marquee customers from discovery through production rollout.
- Design end-to-end architectures integrating LLM orchestration, vector search, tool-calling agents, client data sources, APIs, and security controls.
- Define scalability, resilience, compliance, observability, SLA, and SLO patterns for mission-critical services.
- Run discovery, PoC, pilot, production, and hyper-care delivery phases and create repeatable deployment playbooks.
- Translate business problems into AGI solutions, manage scope, risk, and timelines, and build trusted-advisor relationships with stakeholders.
- Lead technical design reviews, roadmap briefs, architecture artifacts, demonstrations, and platform roadmap feedback.
- Coach engineers on AGI practices, code quality, security, and DevOps, and lead internal guilds on LLM optimization and MLOps.
- Evaluate emerging AI and tooling approaches and pilot them in customer environments.
- Travel to client sites as needed, estimated at approximately 30–40% of the time.
Requirements
- 10–12 years of software engineering experience, including 5+ years in staff, principal, or solutions architect roles.
- Proven experience delivering large-scale, low-latency distributed systems using Python, Java, Go, or C++.
- Hands-on experience with LLM and AI frameworks including LangChain, LlamaIndex, PyTorch, and TensorFlow, plus productionizing ML pipelines.
- Expertise integrating REST and GraphQL APIs, Kafka streaming platforms, SQL and NoSQL stores, and vector databases.
- Excellent client-facing communication, executive-level presentation, and stakeholder-management skills.
- Preferred: Master’s or PhD in AI, Data Science, or Computer Science.
- Preferred: experience shipping RAG or agent-based AI systems in regulated industries.
- Preferred: cloud architecture, data engineering, or security certifications such as AWS SA-Pro or CKA.
- Preferred: background in professional services, forward-deployed engineering, or AI platform product management.
Benefits
- Opportunity to build foundational, practical, auditable, and human-aligned enterprise AI systems with significant ownership and impact.
- Headquartered in Los Altos, California.
- Requires approximately 30–40% travel to client sites, varying by project.
Tech Stack
Categories
Solutions Engineering
