Local Need - Multiple GenAI Technical Solutions Architect / Data Scientist / AgenticAI Egnieer Openings - Bay Area, CA & Austin, TX
VINEET SHARMA
Please share resume to vine...@kanandcorp.com
Need hands-on experience
✅ JD 1: GENAI / AGENTIC AI ENGINEER (PYTHON)
Role: Senior GenAI / Agentic AI Engineer
Experience: 5–10 years
Location: Bay Area / Austin
Key Responsibilities
• Build GenAI-powered applications using LLMs (OpenAI, Claude, Gemini, etc.)
• Design and implement agentic workflows using LangChain, LangGraph, tools & memory
• Develop RAG pipelines using vector DBs (Pinecone, FAISS, Chroma, Weaviate)
• Integrate LLMs with enterprise systems via APIs and event-driven services
• Optimize prompts, latency, cost, and reliability
• Partner with product, data, and platform teams to productionize AI
Required Skills
• Strong Python (5+ years)
• GenAI / LLM integration (2–4 years)
• LangChain / LangGraph / agent frameworks
• REST APIs, microservices
• Vector databases & embeddings
• Cloud (GCP / AWS / Azure)
Nice to Have
• LLM evaluation & guardrails
• Observability for AI systems
• MCP / multi-agent orchestration
✅ JD 2: SENIOR DATA SCIENTIST (APPLIED / GENAI‑AWARE)
Role: Senior Data Scientist
Experience: 6–10 years
Location: Bay Area / Austin
Key Responsibilities
• Perform advanced data analysis to uncover trends, patterns, and drivers
• Build and deploy statistical & ML models (classification, regression, clustering)
• Partner with Data Engineering to productionize features and datasets
• Apply GenAI / LLMs for analytics use cases (insight generation, summarization, recommendations)
• Design experiments and measure impact (A/B testing, KPI tracking)
• Communicate insights to business & product stakeholders
Required Skills
• Strong Data Science fundamentals (statistics, probability, hypothesis testing)
• Python (pandas, NUMPY, scikit‑learn)
• SQL (advanced) for large analytical datasets
• Experience with ML models in production
• Exposure to GenAI / LLMs (prompting, RAG‑enabled analytics)
• Data visualization (Tableau / Power BI / Looker)
Nice to Have
• Feature engineering for ML systems
• Vector embeddings & semantic search
• Snowflake / BigQuery analytics
• Domain knowledge (Sales, Ops, CRM, Supply Chain)
✅ JD 3: GEN AI TECHNICAL SOLUTIONS ARCHITECT
To build and scale AI-powered solutions, you turn designed workflows into working solutions — leveraging existing enterprise tools, MCPs, APIs, and AI platforms to assemble and configure what the team needs. You code when
needed, but your primary value is knowing what's available and wiring it together effectively.
What You'll Do
Build & Prototype
- Assemble AI-powered workflows using existing enterprise tools, MCPs, and APIs
- Write scripts, automations, and glue code to connect systems and fill gaps
- Prototype rapidly — get a working version in front of users fast, then iterate
Evaluate & Advise
- Assess technical feasibility of proposed AI use cases — what's possible with existing tools, what needs IS&T involvement
- Evaluate new tools and capabilities as they become available — is it relevant, is it approved, how does it fit?
- Know when to build vs. when to escalate to IS&T for platform-level support
Integrate & Scale
- Turn one-off prompt solutions into reusable, maintained tools
- Build and maintain the process repository as a living product
- Configure and connect AI solutions to existing BPR and Sales systems
- Ensure solutions are reliable and handle edge cases - Stay current on the enterprise AI landscape — what IS&T ships, what MCPs are available, what's newly approved
Key Qualifications
- 5+ years in a technical role — solutions engineering, technical consulting, or systems integration
- Proficient in Python and/or TypeScript — can write scripts, automations, and integration code
- Hands-on experience with LLMs and AI tools (Claude, ChatGPT, etc.) — prompting, API usage, building AI-powered workflows
- Strong understanding of APIs, data flows, and how enterprise systems connect
- Able to navigate and leverage existing platforms — MCPs, enterprise AI tools, internal tooling — without needing to build them from scratch
- Can translate between technical and business audiences
- Strong prototyping mindset — ship fast, iterate, don't over-engineer
- Self-directed and comfortable with ambiguity
Preferred
- Experience assembling solutions in large enterprise environments with existing tool ecosystems
- Familiarity with data analysis tools (SQL, DuckDB, pandas) for workflow automation
- Background in Sales Operations, CRM, or enterprise business systems
Regards,
Vineet Sharma
Sr Associate - Talent Acquisition
KAnand Corporation
LinkedIn: https://www.linkedin.com/in/vineetshr/
Email: vine...@kanandcorp.com
Web: www.kanandcorp.com
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