Solution Sales Engineer

About

Pienomial is a next-generation AI technology company. Our flagship platform, Knolens, is a deterministic knowledge graph infrastructure that eliminates hallucination, detects contradictions, and provides full claim-level traceability — purpose-built for high-stakes domains including Life Sciences and Finance.

We are looking for a technically strong, client‑facing Solution Sales Engineer who can bridge deep architecture with real business problems — and translate that into compelling, trusted solutions for enterprise customers. This is not a traditional pre‑sales role. You will not just “demo features” — you will shape the solution, prove its value, and own the technical win.

You must understand:

• Why Knolens is fundamentally different from LLM‑based tools
• How to position deterministic, traceable AI in enterprise environments
• How to connect real customer problems to a working, high‑confidence solution

You will be accountable for technical deal success, from discovery through proof‑of‑value and into early deployment alignment.

Key Responsibilities

1. Solution Discovery & Technical Sales

   • Lead deep discovery conversations with enterprise customers (technical, scientific, and business stakeholders)
   • Deconstruct the problem to its first principles
   • Translate ambiguous customer problems into well‑defined solution architectures using Knolens
   • Position Knolens’ knowledge graph + AI memory layer architecture against alternatives (RAG, LLM wrappers, vector search) by reframing the conversation around truth, traceability, and decision risk

2. Solution Design & Value Demonstration

   • Understand customer data ecosystems & define how Knolens integrates into these environments, including:
     • Data ingestion pipelines
     • Knowledge graph construction
     • Traceability frameworks
   • Design end‑to‑end solution blueprints tailored to customer use cases (e.g., HEOR, market access, clinical, CI)
   • Build and present high‑impact demos, POVs, and pilot solutions
   • Clearly articulate:
     • Why the solution works
     • Why it is trustworthy
     • Why alternatives fail in high‑stakes contexts

3. Technical Win Ownership

   • Own the technical close in sales cycles — from first architecture discussion through final validation
   • Address technical objections with depth (data architecture, AI reliability, integration feasibility)
   • Develop written proposals for client submission and work alongside sales leadership to convert opportunities into committed deals

4. Pre‑Sales to Early Delivery Continuity

   • Ensure seamless transition from solution design → implementation readiness
   • Support initial onboarding phases to:
     • Validate solution assumptions
     • Ensure architectural alignment
     • De‑risk delivery

5. Market Feedback & Product Influence

   • Act as the voice of the customer to product and engineering teams
   • Identify repeatable solution patterns that can evolve into productized capabilities
   • Help shape messaging around enterprise AI trust, traceability, and deterministic intelligence

Required Skills & Experience

• Graduate degree in Engineering, Computer Science, or STEM (Life Sciences / Bioinformatics strongly valued where technical depth is demonstrated)
• 5+ years in:
  • Solution engineering / pre‑sales / technical consulting or
  • Solution delivery with strong client‑facing and solution design exposure
• Excellent communication skills (written and verbal)
• Proven ability to:
  • Engage both business and technical stakeholders credibly
  • Translate complex architecture into clear value narratives
• Strong understanding of:
  • Data architecture and integration concepts
  • Knowledge systems (knowledge graphs, ontologies, structured data models)
• Ability to independently handle technical conversations with enterprise architects and domain experts
• Capable of delivering:
  • Solution narratives
  • Architecture walkthroughs
  • Executive‑level value articulation

Desirable Skills

• Experience with AI / ML / NLP systems in enterprise environments
• Familiarity with:
  • Graph databases (Neo4j, etc.)
  • Ontologies (OWL, SNOMED, etc.)
  • Clinical / regulatory data standards (FHIR, MedDRA)
• Exposure to Life Sciences workflows:
  • HEOR, market access, clinical development, regulatory
• Experience building:
  • Proof‑of‑concepts
  • Pre‑sales demos
  • Technical solution proposals

What This Role Is Not

• This is not a project coordinator role with a technical title.
• If your instinct on a hard technical question is to escalate rather than engage, this is not the right role.
• We need someone who can hold their own in a room with a customer's data architect and return to Pienomial's engineering team with precise, actionable information.
• Required attributes:
  • Think architecturally
  • Engage deeply with the product
  • Win trust in the room

Job Location

Pune (on‑site required)