.png){kind=logo}
Vetted Executive & Leadership Professionals in the Bay Area
Pre-screened and vetted in the Bay Area.
Popular Titles
Director-level engineering leader specializing in FinTech, AI, platforms, and mobile
Executive technology leader specializing in AI, LLMs, search, and platform engineering
Senior Full-Stack Engineer specializing in AI automation and LLM-powered products
Kapil Sharma
Executive engineering leader specializing in AI platforms, LLMs, and healthcare SaaS
“Senior engineering leader in healthcare AI who combines org scaling with deep hands-on architecture work. At DriveHealth.ai, they helped evolve isolated workflows into a production-grade intelligent platform, standardizing a shared RAG+DCE architecture while leading teams of 50+ across engineering, AI, platform, QA, and DevOps.”
Dipesh Valia
Director of Engineering specializing in cloud platforms and enterprise SaaS
“Engineering leader focused on large-scale enterprise SaaS and MDM platforms, with experience modernizing monoliths into microservices, improving reliability, and scaling systems to support 15M devices across AWS and Azure. Stands out for combining deep platform architecture work with strong org-building: managed teams up to 45 globally and built a 0-to-1 platform services team to 22 people in under a year.”
Vincent Huebner
Mid-level investment analyst specializing in technology and AI research
“Built ZenDraft and brings an operator's lens to founder sourcing and evaluation. Demonstrated ability to run structured outbound, convert cold outreach into product-shaping conversations and pilot introductions, and manage an early-stage investment-style pipeline with clear decision frameworks.”
Nilesh Dixit
Executive AI engineering leader specializing in agentic AI and enterprise platforms
“Bay Area engineering leader and startup co-founder with a rare mix of deep hands-on architecture experience, large-scale people leadership, and cross-functional product ownership. He helped launch GE Digital's industrial IoT efforts, holds multiple patents in the space, has scaled teams to 60-70 people, and has led both enterprise platform modernization and AI startup product development.”
Inman Breaux
Executive SaaS & AdTech CEO specializing in AI attribution and mobile growth
“Mobile-tech entrepreneur building AppQ (mobile.appq.ai), an agentic mobile SDK that optimizes mobile UX in real time to improve Day 1/Day 7 retention by adjusting levers like ad frequency, difficulty, messaging, and artwork. Previously co-founded an SDK-led mobile ad network (invented push notification ads), scaled to 300K+ SDK integrations, and grew revenue from $7M in 10 months to $50M the following year before exiting in 2020.”
Nergal Issaie
Director of Engineering specializing in AI/ML platforms and cloud systems
“Senior engineering leader from IBM who has built and scaled enterprise AI/GenAI platforms across hybrid and multi-cloud environments, combining executive-level org leadership with hands-on debugging of production distributed systems. Particularly compelling for Director/VP roles needing someone who can unify architecture, platform strategy, and engineering execution across multiple teams.”
Director-level Technology Leader specializing in IoT, cloud platforms, and wireless networking
Executive Business Operations & Chief of Staff specializing in finance, data operations, and cost optimization
Executive SaaS CEO and operator specializing in AI-first growth and Rule of 40 performance
Mid-level Product Marketing leader specializing in AI, gaming, and community growth
Executive engineering leader specializing in FinTech, blockchain, and AI
Director-level product engineering leader specializing in enterprise cloud transformation
Director of Engineering specializing in cloud, microservices, and data-intensive platforms
Entry-level Software Engineer specializing in data pipelines and applied AI
Executive technology leader specializing in AI, cloud, and healthcare transformation
Principal software engineer and technical founder specializing in AI platforms
Shruti Krishnagiri
Executive Engineering Leader & Technical Founder specializing in AI automation platforms
“Founder/CTO who built and shipped a consumer subscription-bundling platform end-to-end (architecture, implementation, testing) and scaled it to thousands of customers and major partners. Previously led a major reliability overhaul at Chan Zuckerberg Initiative for a Google-Docs-like ed-tech product—boosted observability, introduced incident management, and migrated to a Docker-based scalable architecture. Heavy user of AI tools (Cursor/Claude) for development, testing, and code review, with a strong bias toward lightweight, fast-moving execution.”
Prakash Bhanu
Director of Software Engineering specializing in cloud, platform, and FinTech systems
“Senior software engineering leader with broad 0-to-1 product experience spanning web apps, microservices, monoliths, messaging platforms, ML/AI products, and large-scale distributed systems. Notable examples include building a payroll/finance product for cast and crew, a distributed messaging platform, and a Walmart application deployed across multiple CDNs and clouds handling hundreds of TPS, with personal ownership across architecture, design, coding, and support.”
Michael Yudanin
Director-level Engineering Leader specializing in AI/ML and enterprise software
“Engineering leader with 20+ years of experience who still codes daily, currently directing AI-driven knowledge management systems at eGain. He stands out for combining large-scale people leadership with deep technical ownership of LLM/NLI pipelines and for a track record of turning complex operational problems into high-impact systems, including a manufacturing platform that boosted throughput 4x and expanded across 11 plants.”
ABHIJOY SARKAR
Senior AI Engineer specializing in LLMs, agentic systems, and MLOps
“Built and shipped PromptGuard, a production middleware proxy that secures GenAI RAG/agent systems against prompt injection and unsafe tool use using risk scoring, graded policy actions, and least-privilege tool gating. Also replaced LangChain abstractions with a custom state-machine runner for a production voice agent to reduce latency and improve traceability, and delivered a clinic call assistant by converting front-desk/doctor requirements into scenario-based guardrails and measurable evals.”