Senior Full Stack Engineer
Indexed description
Why does MWDN rock?:
Here’s what you can expect when you join MWDN:
- Security: We carefully vet our clients to minimize risks and ensure reliability and timely payments - no fraud or unpleasant surprises.
- Career support: If a project isn’t the right fit, we support you and actively help find new opportunities that match your skills and career goals.
- Legal assistance: We provide guidance on legal matters, including opening and managing your independent contractor or sole proprietorship status, taxes, and related processes.
- Professional development: We offer English courses and professional growth opportunities, as well as team-building events.
What makes this project exciting?:
We’re looking for a senior engineer who can build AI native products on top of reliable, secure, high quality data systems. Someone who has experience shipping production level software for high trust workflows, understands data pipelines and data quality deeply, can deploy safe agentic systems, and knows how to design robust architecture that scales.
This role is for someone who has shipped production software at scale, understands data pipelines and data quality deeply, and knows how to deploy AI systems that are useful, observable, and safe.
You’ll work across the full stack: data ingestion, transformation, storage, APIs, product surfaces, AI workflows, agentic systems, and observability.
What Makes You a Great Fit
You have strong production engineering judgment and can move quickly without compromising reliability, data integrity, and security:
- 8+ years building production software
- Strong experience with TypeScript, React, SQL
- Deep backend architecture, API, data modeling, and production debugging skills
- Significant experience with data pipelines, integrations, or data-heavy systems
- Experience building systems that handle sensitive, regulated, and high trust data
- Production experience shipping robust AI/LLM-powered features
- Strong understanding of evals, hallucinations, malformed outputs, retrieval quality, latency, cost, model drift, and provider risk
- Good judgment about when to use an LLM, when to use retrieval, when to improve the data foundation, and when deterministic code is the better answer
- Excellent written and verbal communication in English
- High ownership, high agency, and low ego
- You know how to build AI systems that are useful without being reckless.
- You understand prompt injection, permission boundaries, data exfiltration risk, secrets handling, audit logs, and human in the loop review. You treat model context as untrusted input and design agent systems with scoped tools, explicit permissions, logging, evals, and graceful failure modes.
- Security is non-negotiable. You should be comfortable with access control, Postgres RLS, PII handling, secrets management, audit trails, least privilege, secure integrations, and safe use of third-party APIs.
- You have built sturdy data pipelines customer facing products rely on
- You care about data correctness before AI or dashboards depend on it
- You can trace a bad number across ingestion, transformation, database, API, UI, and AI context
- You think naturally in failure modes: stale data, duplicate events, schema drift, partial writes, bad joins, expired tokens, provider outages, and malformed model outputs
- You have worked in high trust data environments such as finance, investment, legal, healthcare, or enterprise saas
- You have experience with Supabase, Postgres RLS, Deno, Modal, embeddings, vector search, transcription, GPU workloads, or similar infrastructure
- You have worked with data validation, reconciliation, lineage, observability, or audit systems
- You have experience with AI evals, AI observability, agent testing, or red-teaming AI systems
- Building secure, scalable full-stack product features
- Designing data models, APIs, integrations, and backend architecture
- Creating reliable data pipelines with strong validation and observability
- Shipping high value high trust AI/LLM-powered features
- Building safe agentic workflows with scoped tools, permissions, logging, evals, and failure handling
- Debugging issues across ingestion, transformation, database, API, UI, and AI context
- Designing systems with security, privacy, auditability, and observability
- People-first management with minimal bureaucracy
- A friendly company culture, proven by employees who choose to return
- Flexible working hours
- 29 days of PTO (18 working days per year pluse all national holidays)
- 10 paid recovery days
- Full financial and legal support for independent contractors
- Free English classes, with native speakers or Ukrainian teachers
- Dedicated HR support
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