Get into the weeds with customers — understand their operations, their constraints, and what a good outcome looks like for them

Break down complex business problems into clear solution requirements and map them to Yavar's platform capabilities

Design solution architectures, workflow diagrams, and deployment models grounded in the customer's real environment — not generic slides

Know the product well enough to position it precisely — not just what it does, but why it matters for this customer, in this context

Study the competitive landscape and go into every deal knowing where Yavar wins and why — on technical merit, not just pitch

Handle RFPs, RFIs, and technical questionnaires with clear, well-reasoned responses

Run product demos, architecture walkthroughs, POCs, and technical workshops with confidence

Build solution documents, decks, and architecture diagrams that hold up in a room full of engineers and a room full of executives

Be the technical anchor in pre-sales discussions and translate what you've learned into crisp briefs for product and engineering

Keep up with Yavar's platform roadmap and bring that knowledge into customer conversations

Carry market feedback back to the product organization — you're often the first to hear what customers actually want.

6–8 years in pre-sales, solution engineering, or technical consulting — in enterprise software or AI/ML product companies

A track record of owning pre-sales engagements from discovery through to proposal, not just supporting them

Background in product-based software companies is strongly preferred

This is the core of the role. You should be able to walk into an ambiguous customer situation, ask the right questions, and come out with a logical, defensible solution — not a templated answer.

Strong structured thinking: the ability to separate signal from noise, identify the real constraint, and work backwards from the outcome

Comfortable with incomplete information — you make reasoned calls and explain your thinking clearly

Good grasp of software architecture — microservices, cloud deployments, integration patterns

Familiar with cloud platforms (AWS, Azure, GCP) and how enterprise software gets deployed in practice

Able to talk about AI concepts — LLMs, model inferencing, agentic workflows — without losing a non-technical audience

Working knowledge of Python, JavaScript, or Java — enough to engage credibly with engineering teams

Comfortable with diagramming tools like Lucidchart, Draw.io etc.

You write and speak with clarity — no jargon for its own sake, no over-engineered slides

Equally at ease presenting to a CTO or a business head

You prepare well, listen carefully, and know when to stop talking