Solution Engineer
RelationalAI
WorldwideremotePosted 2 days ago
Skill Required
Solutions-EngineeringTechnical-Sales-EngineeringCustomer-Success-EngineeringEnterprise-AIGTMSolutions-EngineerSolution-Sales-EngineerSolutions-Sales-EngineerSolution-Design-EngineerProduct-Solution-EngineerSolutions-Application-EngineerIT-Solutions-EngineerSolutions-Design-EngineerTechnical-Solutions-EngineerQuery OptimizationSnowflakeanalyticssecuritybuildingEmbedded CExpressdesignCloudGenerative AIandGoAIFulltime
Key highlights
- Base salary range: $170,000 – $200,000.
- 5+ years of production software experience required.
- Fully remote work – work from anywhere in the world.
- Strong SQL and deep familiarity with cloud data platforms (Snowflake, BigQuery, Databricks, Redshift).
- Equity participation offered.
- High‑autonomy ownership model with end‑to‑end responsibility.
Role overview
RelationalAI is building enterprise AI that can understand business context by teaching large language models with private, structured data. The Solution Engineer will embed with customers to deliver end‑to‑end decision‑making systems, own outcomes from discovery through production, and contribute platform improvements back to the product.
Responsibilities
- Embedded inside customers' hardest problems; own the outcome until it works in production, working with executives, domain experts, and data teams to identify high‑impact decisions, model their world in our ontology, formulate the reasoning problem, write PyRel, and ship a solution that runs against real data in their Snowflake account.
- Own outcomes end to end – discovery, modelling, implementation, performance tuning, production hardening, and the measurement that proves it worked. Not a handoff at each stage.
- Build, not describe – design and ship decision solutions on our modelling, reasoning, and learning stack: ontologies over customer data, rules, graph analytics, optimisation formulations, predictive models.
- Fill the gaps yourself – when a customer workflow is blocked on something the platform doesn't do, scope it and build it, then push the general version upstream (read source, form hypothesis, open PR).
- Close the loop with Product – bring back reproductions, patterns, and specific failure modes from each deployment to inform the roadmap.
- Run technical discovery that gets to the truth – conduct workshops, demos, and proofs of concept designed to determine if the problem can actually be solved.
- Leave things better than you found them – document in the repo the same week, turn one‑off work into reusable reference implementations, and avoid long‑running divergent branches.
- Refuse shortcuts that compound – no undocumented config drift, no "it works now" without understanding why it broke, no restarting the service before capturing evidence.
Requirements
- Thrive in ambiguity and move with intent; motivated by deep understanding and meaningful impact.
- Owner, not participant – take full accountability for the outcome and assume responsibility when something is broken.
- Build instinct – open an editor, not a deck; prefer a working prototype on real data over a diagram.
- High conviction, low ego – argue hard for beliefs, be direct about what's wrong, change mind quickly with evidence, and challenge ideas without making it personal.
- Rigorous – root‑cause issues, can explain why it broke and why the fix works; surface symptoms are insufficient.
- Fast in unfamiliar territory – become useful within days in a new codebase, domain, or data model; avoid "I only do backend" mindset.
- High tolerance for friction – navigate messy enterprise environments (broken data, VDI access, security reviews, politics) and keep shipping.
- Impact‑driven – desire the thing you built to remain load‑bearing and operational for years.
- 5+ years building and shipping production software, with experience inside customer or partner environments.
- Demonstrated end‑to‑end ownership: taken something from an ambiguous problem statement to production and can walk through the whole arc, including what went wrong.
- Strong SQL and deep familiarity with cloud data platforms (Snowflake, BigQuery, Databricks, Redshift).
- Strong programming ability – Python primarily; comfort with declarative or logic‑style languages is a real advantage.
- Comfortable reading unfamiliar source code, interpreting stack traces, and debugging systems you didn't write.
- Able to hold your own with both a VP of Supply Chain and a staff data engineer in the same meeting.
- Comfortable operating in high‑autonomy, high‑velocity, low‑instruction environments.
Nice to have
- Built analytical, decision, or reasoning applications that reached production and stayed there.
- Experience with optimization, constraint solving, rule engines, graph algorithms, or ML on structured data.
- Semantic modelling, data pipelines, and governance in real enterprise settings.
- Track record of upstream contribution – features, tools, or abstractions built for one customer that became standard for everyone.
- Prior experience in enterprise technology, AI, or analytics platforms.
Benefits
- Work from anywhere in the world (fully remote).
- Competitive base salary range of $170,000 to $200,000 plus equity.
- Open PTO, flexible schedules, and recharge weeks.
- Global benefits, mental‑health support, and learning stipends.
- Transparent, inclusive, globally connected culture that values curiosity, excellence, and impact.
- Regular team offsites and global events to build strong connections.
- Culture of transparency and knowledge‑sharing via standups, fireside chats, and open meetings.
Additional details
- Company mission: solving AI's challenge of teaching large language models the logic, semantics, and business context of the modern enterprise through Superalignment, relational knowledge graphs, and neuro/symbolic‑relational reasoners.
- The Role narrative: each engagement produces a customer‑facing decision system and internal platform improvements; the role exists to deliver both, not just consulting work.
- Clarifications of what the role is NOT: not demo‑and‑hand‑off pre‑sales, not staff augmentation, not advisory, not a support role.
- Hiring process: technical screen, system navigation/extending exercise, problem‑decomposition session on realistic customer scenario, and ownership conversation with hiring manager.
- Country hiring guidelines: remote roles worldwide, with location‑specific eligibility and visa support; People Operations can answer location questions.
- Application call‑to‑action and privacy policy links for EU and California residents.
- Equal opportunity statement affirming non‑discrimination based on protected characteristics.
- Original posting source: Himalayas.