Careers at Satinash
Build work people can verify.
Explore the disciplines behind a proof-first AI workspace. Each role profile keeps the work, ownership, and application path in one place.
Explore roles Role directory
Find where your craft fits.
18 role profiles across the teams that build, evaluate, explain, and operate the product.
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Platform & trust Platform DevOps Engineer
Own the deployment, observability, and runtime foundations behind the product's public and app surfaces.
You will keep releases boring, infrastructure visible, and production paths easy for engineers to operate.
Technical focus
- Bun, Astro, Django, worker, and static-site release pipelines with explicit environment contracts.
- Native TLS, mapped-host, Caddy, Linux service, and post-deploy smoke-test ownership.
- Build-cache, artifact, rollback, and deploy-preflight improvements that reduce release risk.
What you would own
- Maintain CI, deployment automation, TLS, and environment contracts for the website and app.
- Improve monitoring, incident response, and operational playbooks across the native stack.
- Partner with backend and frontend teams to make release paths simpler and safer.
What you would bring
- Strong production experience with Linux, CI/CD, web hosting, and infrastructure-as-code workflows.
- Comfort debugging network, certificate, build, and runtime issues across services.
- A taste for simple operational systems, clear runbooks, and measurable reliability.
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Platform & trust Site Reliability Engineer
Build the operational muscle that keeps the product responsive as teams depend on it for daily knowledge work.
You will turn reliability goals into practical telemetry, alerts, and recovery paths.
Technical focus
- Service-level indicators for API latency, stream health, worker queues, connector syncs, and static website uptime.
- Structured logs, metrics, traces, alert thresholds, and runbook automation for production incidents.
- Database, queue, cache, and long-running task behavior under load and failure conditions.
What you would own
- Define service-level signals for website, API, worker, and connector paths.
- Create incident tooling and dashboards that make failures fast to isolate.
- Lead resilience exercises and post-incident improvements with engineering teams.
What you would bring
- Experience operating customer-facing SaaS systems with meaningful uptime expectations.
- Fluency with logs, metrics, traces, queues, and database-backed application systems.
- Clear written communication for incidents, follow-ups, and technical decision records.
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Platform & trust Security Engineer
Protect customer knowledge, credentials, connectors, and administrative control planes.
You will help the product earn trust by making security work practical for builders and operators.
Technical focus
- OAuth flows, session boundaries, connector credentials, service-account paths, and scoped access controls.
- Threat modeling for retrieval, file ingestion, admin operations, secrets handling, and external tool execution.
- Audit trails, abuse prevention, secure defaults, incident response, and security regression coverage.
What you would own
- Review authentication, authorization, connector, secret, and deployment flows.
- Lead threat modeling, security testing, and remediation planning for product features.
- Improve secure defaults, auditability, and operational guardrails across the stack.
What you would bring
- Experience securing SaaS applications, APIs, cloud infrastructure, and identity flows.
- Comfort partnering with engineers to land pragmatic fixes and durable tests.
- Strong written communication for risks, decisions, and incident-ready documentation.
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Platform & trust Quality Engineering Lead
Raise the quality bar for product workflows that combine data, AI, permissions, and UI.
You will turn high-risk behavior into clear test strategy, automation, and release confidence.
Technical focus
- Backend pytest, Bun frontend tests, Astro checks, Playwright/browser smoke tests, and CI release gates.
- Fixture hygiene, API contract assertions, user-visible state checks, and high-signal regression coverage.
- Risk-based validation plans for streaming, retrieval, ingestion, billing, auth, and admin workflows.
What you would own
- Design test strategy for cross-surface features and critical regression paths.
- Build automation around user-visible contracts, API behavior, and release gates.
- Coach engineers on concise, behavior-focused tests that avoid brittle copy assertions.
What you would bring
- Experience leading quality strategy for complex web applications.
- Strong automation skills across API, frontend, and integration test layers.
- A practical understanding of risk, coverage, and when broader validation is warranted.
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Product engineering Full-Stack Product Engineer
Shape end-to-end product workflows from governed knowledge setup to polished user-facing answers.
You will work across UI, APIs, tests, and product behavior without losing sight of the user.
Technical focus
- TypeScript interfaces, React/Astro views, Django APIs, and PostgreSQL-backed product contracts.
- Dataset, Core, connector, chat, and admin workflows that need clear state and permission boundaries.
- Focused unit, integration, and browser tests that guard behavior rather than static copy.
What you would own
- Build durable frontend and backend features for knowledge work, admin, and collaboration flows.
- Write targeted tests that prove behavior, not just rendered copy.
- Refine existing owners instead of adding parallel implementations.
What you would bring
- Strong TypeScript and Python experience in production web applications.
- A track record of shipping scoped features with clean interfaces and reliable tests.
- Comfort reading an existing codebase before choosing the implementation path.
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Product engineering Frontend Engineer, Design Systems
Evolve the product's visual system, interaction patterns, and performance-sensitive product surfaces.
You will help make complex AI workflows feel calm, legible, and fast.
Technical focus
- React, TypeScript, CSS tokens, responsive layouts, accessible controls, and dense dashboard ergonomics.
- Buffered text input, debounced derived state, optimistic UI, and route-level rendering performance.
- Evidence views, graph detail panels, form-heavy admin screens, and reusable product chrome.
What you would own
- Build reusable UI patterns for navigation, forms, data-heavy views, and evidence surfaces.
- Improve accessibility, responsiveness, and input performance across the web app.
- Partner with product design to keep visual decisions consistent and purposeful.
What you would bring
- Deep React, TypeScript, CSS, accessibility, and browser behavior experience.
- Strong judgment around component boundaries, design tokens, and interaction states.
- Ability to validate UI changes with automated and visual checks.
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Product engineering Backend Engineer, Knowledge Graph
Design backend systems that connect documents, datasets, Cores, tools, permissions, and evidence trails.
You will make the graph of knowledge explainable, secure, and fast enough for real teams.
Technical focus
- Django service owners, PostgreSQL schema design, pgvector-backed document profiles, and API serializers.
- Document lifecycle state, dataset links, Core permissions, retention, and retrieval eligibility contracts.
- Migration-safe canonical SQL, retained schema patches, and regression tests for state transitions.
What you would own
- Improve data models and APIs for retrieval, document state, graph details, and Core configuration.
- Write clear tests around permissions, lifecycle states, and user-visible contracts.
- Keep schema and runtime logic consolidated in the native service owners.
What you would bring
- Production experience with Python, Django or similar frameworks, PostgreSQL, and API design.
- Comfort reasoning about data ownership, lifecycle transitions, and permission boundaries.
- A disciplined approach to tests, migrations, and rationale comments for non-trivial logic.
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Product engineering Product Manager, AI Workflows
Guide the experiences that help people ask better questions, inspect evidence, and act with confidence.
You will translate complex AI capability into workflows that users can understand and repeat.
Technical focus
- Cores, datasets, retrieval, chat orchestration, tool execution, source trails, and admin governance.
- Product specs that turn AI behavior into testable contracts, acceptance criteria, and measurable outcomes.
- Telemetry, support patterns, research interviews, and eval data that shape workflow priorities.
What you would own
- Define product requirements for Cores, chat, retrieval, tool use, and evidence review.
- Work with design and engineering to make AI behavior understandable and testable.
- Use research, support signals, and product metrics to prioritize the roadmap.
What you would bring
- Experience managing technical products with AI, data, search, developer tools, or enterprise workflows.
- Strong written product thinking and ability to clarify ambiguous user needs.
- Comfort making tradeoffs across usability, correctness, reliability, and scope.
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Product engineering Product Designer
Design calm product surfaces for dense knowledge workflows, admin controls, and AI answer review.
You will make the product feel powerful without making users fight the interface.
Technical focus
- Information architecture for knowledge setup, evidence inspection, connector configuration, and admin workflows.
- Design tokens, accessible interaction states, responsive layouts, and component behavior for dense SaaS tools.
- Prototypes that clarify AI uncertainty, citation trust, tool activity, loading states, and error recovery.
What you would own
- Design core workflows, interaction states, information architecture, and visual systems.
- Prototype complex AI and data experiences with attention to evidence and trust.
- Partner tightly with engineering to ship polished, responsive, accessible UI.
What you would bring
- A portfolio showing sophisticated product design for complex tools or data-heavy apps.
- Strong systems thinking around components, states, hierarchy, and interaction patterns.
- Comfort working from product intent through implementation details.
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Applied AI AI Retrieval Engineer
Improve how the product retrieves, ranks, cites, and explains knowledge from customer-controlled sources.
You will make answers more useful by making retrieval more precise and auditable.
Technical focus
- Embedding model selection, chunking profiles, vector search, reranking, citation spans, and source filtering.
- Retrieval diagnostics for stale documents, permission scope, ingestion settings, and model-dimension mismatches.
- Offline eval sets, query taxonomies, recall/precision tradeoffs, and answer-grounding review workflows.
What you would own
- Tune retrieval, reranking, chunking, and citation strategies for diverse knowledge sets.
- Create evaluation datasets and diagnostics for answer quality and source grounding.
- Partner with product engineers to expose retrieval behavior in understandable UI.
What you would bring
- Hands-on experience with embeddings, ranking systems, LLM retrieval, and evaluation loops.
- Strong Python skills and comfort reading production service code.
- Practical skepticism about magic: you prefer measured improvements and visible evidence.
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Applied AI AI Agent Systems Engineer
Build orchestration systems that let models use tools, knowledge, and policies without brittle shortcuts.
You will help make AI workflows trustworthy when users ask complex, multi-step questions.
Technical focus
- Structured tool schemas, planner budgets, runtime observations, artifact contracts, and UI message streams.
- MCP-style tool exposure, connector capability metadata, dependency handling, and model-agnostic tool choice.
- Evaluation harnesses for tool calls, final-answer repair, source scope, and multi-step task reliability.
What you would own
- Design planner, tool-use, and final-answer behavior around structured contracts.
- Evaluate model behavior across tool schemas, source scopes, and workflow constraints.
- Remove brittle routing logic in favor of generic, observable runtime decisions.
What you would bring
- Experience building LLM applications with tool use, evaluation, and production constraints.
- Strong backend engineering fundamentals and comfort debugging model-system interactions.
- A preference for explicit contracts over prompt-only or keyword-based behavior.
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Applied AI ML Evaluation Engineer
Create measurement systems that show whether the product answers are grounded, useful, and safe to trust.
You will give product and engineering teams the signal they need to improve AI quality.
Technical focus
- Golden datasets, rubric-based review, sampling strategy, failure taxonomies, and regression dashboards.
- Metrics for retrieval quality, citation correctness, answer completeness, refusal behavior, and tool success.
- Python analysis workflows that connect product telemetry, fixture data, and model-output review.
What you would own
- Build offline and online eval workflows for retrieval, tool use, citations, and answer quality.
- Create fixtures, dashboards, and review loops that make regressions visible.
- Collaborate with AI engineers to turn failures into targeted product improvements.
What you would bring
- Experience designing evaluations for LLM, search, retrieval, or recommendation systems.
- Strong Python and data analysis skills with a bias toward reproducible methods.
- Clear judgment around statistical signal, qualitative review, and product impact.
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Experience & growth Technical Writer
Write docs that help users understand Cores, datasets, connectors, AI behavior, and admin operations.
You will make the product easier to adopt by turning complex systems into clear guidance.
Technical focus
- Connector setup guides, Core configuration docs, API-adjacent references, admin runbooks, and troubleshooting flows.
- Source-grounding, ingestion, retrieval, permission, and model-behavior explanations for technical readers.
- Release notes and migration-style guidance that map product changes to user-visible effects.
What you would own
- Create product docs, setup guides, release notes, and troubleshooting material.
- Partner with engineering and support to keep documentation accurate as behavior changes.
- Develop examples that show how real teams use the product in daily workflows.
What you would bring
- Experience documenting technical SaaS, AI, data, security, or developer products.
- Ability to test workflows yourself and ask precise questions when behavior is unclear.
- Clear, plain writing that respects expert readers without assuming too much context.
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Experience & growth Developer Relations Engineer
Help technical users understand, extend, and trust the product's connectors, tools, and AI workflows.
You will turn product capability into examples, demos, talks, and feedback loops.
Technical focus
- Sample connector workflows, MCP-style tool demos, local setup guides, and technical launch examples.
- Developer-facing tutorials that explain schemas, auth setup, retrieval behavior, and evidence inspection.
- Community feedback loops that turn integration pain into concrete product and documentation improvements.
What you would own
- Build sample workflows, technical content, and demo environments for developers and admins.
- Represent user feedback to product and engineering with clear evidence.
- Support launches, events, and community conversations around governed AI knowledge work.
What you would bring
- Hands-on engineering background with strong communication instincts.
- Experience creating developer-facing content, demos, or community programs.
- Comfort explaining AI and integration concepts without hype or hand-waving.
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Experience & growth Solutions Engineer
Map customer workflows to the product Cores, connectors, permissions, and rollout plans.
You will help prospective and new customers see a practical path from scattered knowledge to governed answers.
Technical focus
- Identity, connector authentication, data-source mapping, permission design, and deployment-readiness reviews.
- Technical discovery that turns security, compliance, and workflow constraints into feasible solution plans.
- Pilot architectures that cover source scope, model choice, retrieval quality, and admin operating model.
What you would own
- Run discovery, demos, pilots, and technical solution design for customer teams.
- Translate customer requirements into product feedback and implementation plans.
- Partner with sales, success, and engineering to unblock complex deployments.
What you would bring
- Experience in solutions engineering, sales engineering, consulting, or technical onboarding.
- Strong understanding of SaaS integrations, identity, security, and data workflows.
- Ability to communicate with executives, admins, and hands-on technical users.
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Experience & growth Customer Success Manager
Help teams adopt the product, expand usage, and turn knowledge workflows into lasting habits.
You will make sure customers get value after launch, not just during the sale.
Technical focus
- Workspace configuration, Core rollout, connector adoption, usage signals, and health-score instrumentation.
- Customer enablement for admins, champions, security reviewers, and hands-on knowledge workers.
- Escalation patterns that preserve context across support, product, solutions, and engineering teams.
What you would own
- Own onboarding, adoption plans, success reviews, and renewal readiness for customer accounts.
- Identify workflow gaps and coordinate with product, support, and solutions teams.
- Create repeatable customer playbooks for common rollout patterns.
What you would bring
- Experience managing customer relationships for B2B SaaS or technical products.
- Strong organization, empathy, and executive-ready written communication.
- Comfort learning technical workflows well enough to guide practical adoption.
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Experience & growth Growth Marketing Manager
Build demand programs that explain the product to people who need governed, source-grounded AI work.
You will connect positioning, campaigns, content, and measurement into a coherent growth engine.
Technical focus
- Lifecycle campaigns, attribution, SEO, product analytics, CRM hygiene, and funnel instrumentation.
- Messaging for retrieval, citations, governance, connectors, admin controls, and technical buyer concerns.
- Experiment design that connects campaign hypotheses to qualified pipeline and product-qualified signals.
What you would own
- Plan and execute campaigns across content, lifecycle, paid, events, and partner channels.
- Measure funnel performance and turn signal into sharper messaging and better experiments.
- Work with product, sales, and customer teams to tell grounded stories from real workflows.
What you would bring
- Experience growing B2B SaaS, AI, data, developer, or productivity products.
- Strong campaign execution skills with comfort in analytics and experimentation.
- A clear writing style and low tolerance for vague AI marketing claims.
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Experience & growth People & Talent Lead
Build the hiring and people systems that help the product scale with clarity and care.
You will shape how we attract, evaluate, onboard, and support the team.
Technical focus
- Structured interview loops, role scorecards, hiring analytics, ATS hygiene, and onboarding instrumentation.
- Technical recruiting calibration across infrastructure, backend, frontend, AI, security, and go-to-market roles.
- People programs that keep feedback, leveling, compensation, and manager workflows lightweight but consistent.
What you would own
- Run recruiting operations, candidate experience, onboarding, and people programs.
- Partner with leaders to define roles, interview loops, leveling, and feedback practices.
- Create lightweight systems that keep hiring fair, fast, and respectful.
What you would bring
- Experience leading recruiting or people operations at a growing technology company.
- Strong judgment around structured interviewing, candidate communication, and team health.
- A builder mindset: you prefer clear, usable process over heavy policy theater.
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