PravoTech is a product IT company. We are developing PravoConsultant — an AI service that helps people go from a life situation to a legal outcome: deal with debt, dismissal, divorce, get an action plan, or prepare a document. In September 2026, the service was accessed approximately 85,000 times.
We are looking for a product engineer-leader who will turn AI agent capabilities into an understandable and in-demand product: from the first request to the result, repeat visits, and payment.
In this role, you will independently design and develop key scenarios in React/TypeScript and Python, lead a team, and be responsible for user metrics. Experience with the entire scenario is important to us: interface, product services, integrations, and reliable result delivery.
What you will be doing
- Developing the user journey: entry, first request, clarifying questions, receiving calculations, plans, or documents, returning with a new situation.
- Developing a chat with streaming, a case library, an editor, and document export.
- Creating shared interface components for agents: questionnaires, calculations, plans, documents, and comparisons. New features should be available to users without separate development of each interface.
- Designing and developing product services: authorization, access for organizations, tariffs, billing, limits, analytics, and feedback.
- Ensuring the reliability of long-running processes of 10-30 minutes: statuses, resumption, cancellation, retries without operation duplication, and recovery after connection loss.
- Defining contracts between the interface, API gateway, and agent services, ensuring backward compatibility.
- Identifying points of loss in funnels, testing hypotheses, conducting A/B tests, and developing mechanics for activation, retention, monetization, and growth through users.
- Using AI agents for development and substantively checking the code they create.
- Hiring and developing engineers, organizing regular releases.
One of the first tasks is to define the boundary of responsibility within the API gateway and fix contracts between teams, together with the Circle Lead for Agents.
What results the role is responsible for
- Growth in the share of users who received the first useful result.
- Reduction in time and number of steps to the result.
- Repeat visits and user retention.
- Conversion to payment and retention of paying users.
- Cost of a successful result and tariff economics.
- Reduction in interrupted launches, streaming disconnections, and lost responses.
Legal quality, search, RAG, and model infrastructure are developed by other teams. The Product Lead understands their structure and impact on user experience, negotiates integrations, and verifies changes at the intersection of systems.
What we expect from you
- From 6 years of production development, including at least 3 years of TypeScript/React and at least 3 years of Python. You continue to write code independently.
- Experience launching a user product with measurable results: you can name the metric, values before and after, the timeframe, and your contribution.
- Practical experience with funnels and onboarding, monetization or user-driven growth, experiments, and A/B tests.
- Experience releasing AI interfaces for real users: streaming responses, long tasks with progress, clarifying questions within scenarios, displaying sources.
- Experience designing user products on microservices: contracts and versioning, events, idempotency, reliability of long operations.
- Confident review of Python services on FastAPI, asyncio, and Pydantic, as well as TypeScript/React. Ability to find errors in states, concurrent operations, and authorization.
- Using AI agents as the primary development tool: from idea to working scenario with result verification.
- Understanding of LLM systems: RAG, tool calling, token costs, latency, quality assessment, and regressions when changing models or prompts.
- Experience with AI system observability: Langfuse or equivalent, call tracing, evaluations, costs, prompt versions; OpenTelemetry.
- Experience leading a team of 4+ engineers: hiring, task assignment, development process, code reviews, and employee development.
Will be an advantage
- Deep knowledge of Python: profiling, memory, internal workings of asyncio.
- Practical experience building RAG, search, and assessing model quality.
- Declarative interface where the agent describes the necessary elements, and the application displays them through ready-made components.
- Billing with variable costs: token limits, expense tracking, and reconciliation of charges.
- Real-time collaborative document editing.
- OAuth 2.1 and connecting external AI clients via MCP.
- SLO and alerts for long-running scenarios.
- Go at the code reading level, experience with on-premise product delivery.
- Experience with mobile development or React Native.
Legal education, model training, and ML research are not required. The mobile application is a later direction; experience developing it is not mandatory.
Our Stack
- Frontend: TypeScript, React 19, Next.js 16, TanStack Query, Tailwind, shadcn, zod, Playwright, Vitest.
- Backend: Python 3.14, FastAPI, Pydantic v2, asyncio, SQLAlchemy, Alembic.
- Events and Integrations: NATS JetStream, HTTP, SSE, MCP, OAuth.
- AI: FastMCP, tool calling, LiteLLM, OpenRouter.
- Data: PostgreSQL, MongoDB, Redis, S3.
- Observability and Experiments: Langfuse, OpenTelemetry, Prometheus, Grafana, PostHog, Flipt.
- Infrastructure: Docker, Kubernetes, Argo CD, GitLab CI.
Conditions
- Remote or hybrid format; office in Moscow on Bolshaya Polyanka.
- Employment according to the Labor Code of the Russian Federation.
- Voluntary Medical Insurance with dental coverage.
- Autonomy in technical and product decisions, the opportunity to influence service development and team formation.
Introduction Stages
HR Interview → Technical Interview → Circle Leader Election.
The final stage is an online meeting where you will present your experience, leadership approach, and product development vision. We will provide preparation materials in advance.
In your application, it would be helpful to briefly describe:
- What user AI product have you launched and what did you implement personally.
- What metric have you improved, by how much, and over what period.
- What tasks are you currently solving in Python and React/TypeScript.
- What team have you led and whom have you hired.
