Empat

An AI consulting group that builds serious, production-grade systems for companies ready to operationalize artificial intelligence across their business. We do not build gimmicks. The main focus is on custom AI solutions that integrate directly into operations and drive measurable results.

We're looking for an AI Engineer for one of our clients. This is a hands-on role for someone who works across the full stack to turn ambiguous, real-world business problems into working AI-powered products — not someone who only experiments with AI in isolation.

This role is for someone who can take a vague business challenge, independently define the AI-driven approach, and build it end to end — from backend logic to frontend interface. Example use case: building a permitting tool that helps manage government permits (air permits, water permits, etc.). You'll work at the intersection of LLMs, multimodal models, and full-stack product engineering, in a fast-paced, startup-style environment with limited structure and high ownership expectations.

Your responsibilities will include:
- Building LLM-powered tools for complex, often domain-specific product use cases;
- Developing multimodal AI applications (vision, audio, or other modalities as needed);
- Full-stack feature development combining a Python backend with a React frontend;
- Breaking down new, ambiguous business problems into concrete AI-driven engineering solutions;
- Working independently to scope, design, and ship AI features without heavy oversight;
- Collaborating with technical, infrastructure, and commercial stakeholders on the client side.

What we expect from you:
- Hands-on experience building with LLMs in production;
- Comfort working across the full stack — backend (Python) and frontend (React);
- Ability to take a vague problem and independently define and build the AI solution;
- Strong software engineering fundamentals;
- Self-driven mindset — takes ownership and moves without constant direction;
- Fast learner who picks up new technical contexts quickly;
- Comfortable with ambiguity, fast pace, and limited structure (startup mindset).

Nice to have:
- Experience with multimodal models (vision, audio, etc.);
- Prior startup or fast-paced product environment experience;
- Familiarity with agentic workflows or tool-use patterns;
- Experience in complex domain-specific tooling (e.g. legal, compliance, permitting).

We offer:
- Direct influence on production AI systems used in real business operations;
- Close collaboration with the client's product and engineering teams;
- Opportunity to build real, shipped AI products — not prototypes.

The company is building the control layer for an energy-constrained world — deploying AI, machine learning, and reinforcement learning to optimize HVAC systems, industrial equipment, and large-scale energy loads across commercial buildings, factories, hospitals, and data centers. The focus is on real, measurable impact: autonomous control systems that drive 20–30%+ energy savings in production environments.

We're looking for a BMS Control Engineer / Forward Deployment Engineer (TPM) who will join the team. This is a hands-on role for someone who doesn't just design building automation systems, but has deployed, commissioned, and optimized them in real-world infrastructure.

This role is for someone who takes full ownership of field deployments — from site discovery to production rollout. You'll work at the intersection of BMS/BAS systems, HVAC controls, and AI-driven optimization, deploying autonomous control systems across commercial buildings, factories, hospitals, and data centers.

Your responsibilities will include:

• Own deployments end-to-end: site discovery, integration, commissioning, validation, and rollout;
• Install, configure, and commission BAS/BMS and PLC-integrated systems;
• Deploy gateways, sensors, submeters, and communications infrastructure;
• Perform startup, point-to-point testing, and controls validation;
• Interface with AHUs, RTUs, chillers, boilers, pumps, cooling towers, and VFDs;
• Integrate through BACnet (IP & MS/TP), Modbus, LON, and IP networks;
• Work with Niagara, Siemens, Honeywell, Johnson Controls Metasys, Delta, and other BAS platforms;
• Configure addressing, routing, communications, and device connectivity;
• Diagnose controls hardware, wiring, networking, protocol, and sensor issues;
• Support deployment of AI-driven and RL-driven control strategies;
• Own deployment schedules, communications, milestones, and execution;
• Coordinate customers, contractors, vendors, and internal engineering teams;
• Maintain deployment plans, commissioning reports, diagrams, and as-built documentation.
   

What we expect from you:

• Degree in Electrical Engineering, Mechanical Engineering, HVAC, or related discipline — or equivalent BAS/PLC/SCADA/DCIM experience;
• 2+ years of hands-on BACnet experience (IP & MS/TP);
• 2+ years of Modbus experience;
• 2+ years of HVAC Controls / DDC / BMS experience;
• Strong understanding of BMS/DDC systems, PLCs, PID loops, hydronics, and refrigeration;
• Experience with BAS platforms: Niagara (Tridium), Siemens, Honeywell, Johnson Controls Metasys, Delta;
• Hands-on commissioning and troubleshooting experience in the field;
• Ability to work independently and take ownership in customer-facing environments.
   

Nice to have:

• Niagara (Tridium), EPA 608, NATE, or OSHA certifications;
• Experience in industrial facilities, healthcare, mission-critical environments, or data centers;
• Exposure to IoT, edge computing, SCADA, or DCIM platforms;
• Experience with LON protocol and IP networking in BAS contexts.
   

We offer:

• Full-time engagement on a high-impact infrastructure project;
• Remote-friendly with on-site deployment work at client facilities;
• Direct work with cutting-edge AI and reinforcement learning applied to real-world systems;
• Measurable impact — 20–30%+ energy savings across live deployments;
• Opportunity to help define the future of autonomous building and industrial control systems.

Build data-intensive systems that actually scale. Own distributed processing, not just services. Shape how large-scale data flows power products.
 

We’re looking for a Senior Scala / Data Engineer for one of our clients — a company operating in a data-heavy, distributed systems environment. This is a hands-on role for someone with a strong Scala background who has built and optimized high-performance data systems in production.

This role is for someone who takes full ownership of distributed data systems — from architecture to performance. You’ll work on complex, large-scale data processing challenges where efficiency, scalability, and fault tolerance are critical.
 

Your responsibilities will include:

• Build and optimize distributed data processing systems using Scala;
• Design and implement high-throughput, low-latency data pipelines;
• Work with big data frameworks (e.g., Spark) and distributed architectures;
• Develop and maintain scalable backend services for data-intensive workloads;
• Optimize performance of data processing jobs and infrastructure;
• Ensure fault tolerance and resilience of distributed systems;
• Implement monitoring, logging, and observability for data pipelines;
• Collaborate with engineering teams to design scalable system architectures;
• Contribute to cross-functional backend and data engineering efforts;
• Ensure high standards of code quality, performance, and reliability.
   

What we expect from you:

• Strong experience with Scala in production environments;
• Proven experience as a Senior Data Engineer or Backend Engineer in data-heavy systems;
• Strong understanding of distributed systems and parallel processing;
• Experience with big data technologies (Spark, Kafka, etc.);
• Strong knowledge of JVM ecosystem and performance tuning;
• Experience building high-load, scalable systems;
• Strong system design and architectural thinking;
• Ability to work independently and take ownership;
• Strong problem-solving skills in complex, distributed environments;
• English level: B2+ (C1 preferred);
• Availability to work in EU timezone.
   

Nice to have:

• Experience with functional programming paradigms;
• Experience with cloud infrastructure (AWS / GCP);
• Experience with stream processing frameworks (Flink, Akka Streams);
• Background in low-latency or real-time systems;
• Experience in niche or hard-to-hire tech domains.
   

We offer:

• Six-month full-time contract engagement;
• Remote work with overlap in US business hours;
• High-impact project with direct influence on production AI systems;
• Close collaboration with client’s product and engineering teams;
• Opportunity to build core infrastructure for real-world AI applications — not prototypes.

We’re looking for a Senior Machine Learning Engineer to design and scale production ML systems that power real-time personalization and decision-making at scale.

In this role, you’ll own the full ML lifecycle—from transforming raw behavioral data into meaningful features, to deploying low-latency prediction APIs, to building the observability needed to keep models reliable in production.

This is a great opportunity for someone with strong applied ML and MLOps expertise who enjoys solving complex engineering challenges and building scalable, high-impact systems.

Your responsibilities will include:

• Build and productionize ML models for ranking, personalization, and customer engagement.
• Develop pipelines that transform behavioral, demographic, and contextual signals into online and offline features.
• Design and deploy low-latency APIs and decision services for real-time decision-making.
• Implement experimentation frameworks, including A/B testing and exploration-exploitation strategies.
• Operationalize the ML lifecycle: automated training, CI/CD for models, artifact and feature versioning, and online/offline parity.
• Build observability into ML systems by monitoring data quality, model drift, and decision outcomes, and triggering retraining when needed.
• Establish closed feedback loops that connect decisions to business outcomes (e.g. conversions, engagement, fatigue signals such as unsubscribes).
• Collaborate closely with product and engineering teams to balance personalization, compliance, and business value in real-world systems.

What we expect from you:

• 5+ years of experience in applied ML engineering (recommendation systems, personalization, ranking, or advertising systems).
• Strong proficiency in Python or Go, SQL, and modern ML frameworks such as TensorFlow, PyTorch, or similar.
• Strong understanding of MLOps best practices, including CI/CD for ML, containerization (Docker), orchestration (Kubernetes, Airflow, Kubeflow), model registries, and monitoring frameworks.
• Familiarity with cloud ML platforms such as Vertex AI, SageMaker, or similar, and data warehouses like BigQuery, Snowflake, or Redshift.
• Experience deploying real-time ML systems, including low-latency serving, feature stores, and event-driven architectures.
• Understanding of multi-objective optimization and trade-offs in personalization systems.
• Comfort working cross-functionally in a dynamic startup environment with the overlap within USA time zone.
• Strong spoken and written English communication skills.

Nice to have:

• Experience in martech, adtech, CRM, or large-scale personalization platforms.
• Exposure to bandit algorithms, reinforcement learning, or causal inference for adaptive decision-making.
• Experience building systems serving millions of users at scale.
• Hands-on experience with Google Cloud Platform (GCP).
• Familiarity with observability tools such as Prometheus, Grafana, Evidently, WhyLabs, or Great Expectations for monitoring data and model health.

What we offer:

• Interesting projects and technical challenges that support both professional and personal growth.
• A long-term project with stability and impact.
• A flexible, results-oriented schedule with hybrid or remote work options.
• A comfortable, modern office in Kyiv with generator and battery backup.
• Competitive salary, medical insurance, and a supportive onboarding/trial period.
• Team-building events, including parties, online activities, picnics, and more.
• The opportunity to work in a Top Employer company (DOU 2025).

An AI consulting group that builds serious, production-grade systems for companies ready to operationalize artificial intelligence across their business. We do not build gimmicks. The main focus is on custom AI solutions that integrate directly into operations and drive measurable results. 

 

We’re looking for a Senior AI Engineer for one of our clients. This is a hands-on role for someone who doesn’t just experiment with AI, but has built, deployed, and optimized real AI systems in complex, production environments.

 

This role is for someone who takes full ownership of AI systems — from architecture to performance. You’ll work at the intersection of LLMs, distributed data processing, and backend systems, building scalable AI pipelines and knowledge systems in a high-impact environment where performance, reliability, and flexibility (including airgapped deployments) matter.

 

Your responsibilities will include:

• Design and build distributed data pipelines (Apache Beam, Python) for large-scale document and model processing;
• Implement horizontally scalable LLM-powered extraction workflows across thousands of entities;
• Build runner-agnostic pipelines that run across multiple environments (local, cloud, on-prem);
• Design and implement entity resolution and cross-referencing systems with confidence scoring;
  Architect and build graph-based Knowledge Bases (Dgraph or similar), including schema design and query optimization;
• Develop pluggable LLM extractor frameworks (classification, relationships, completeness, document linking);
• Build abstraction layers for LLM providers (Anthropic Claude, Google Gemini, local models via Ollama/vLLM);
• Optimize LLM usage for cost, latency, and reliability in production environments;
• Design and implement backend service layers (Go-based APIs) connecting AI pipelines with agent systems;
• Ensure observability, debugging, and performance monitoring across distributed AI systems;
• Package and deploy systems using Docker (docker-compose, containerized environments);
• Collaborate directly with client teams on integrations, validation, and production rollout.
  
   

What we expect from you:

• 5–8+ years of experience in AI Engineering, Data Engineering, or Applied ML Infrastructure;
• Expert-level Python;
• Strong experience with distributed processing frameworks (Apache Beam preferred; Spark/Flink acceptable);
• Hands-on experience integrating LLMs in production (prompting, orchestration, provider abstraction);
• Experience with graph databases (Dgraph, Neo4j, JanusGraph, or similar);
• Strong understanding of distributed systems, parallel processing, and large-scale data pipelines;
• Solid SQL and data modeling fundamentals;
• Experience with Docker and containerized deployments;
• Experience with cloud platforms (GCP preferred, AWS/Azure acceptable);
• Strong backend/system design mindset (performance, scalability, reliability);
• Ability to work independently and take ownership without micromanagement;
• Strong problem-solving skills in complex, ambiguous environments;
• English level: B2+ (C1 preferred);
• Availability to overlap with US business hours.
  
   

Nice to have:

• Working experience with Go (for API/service layer contributions);
• Experience with local LLM inference (Ollama, vLLM, TensorRT-LLM);
• Experience deploying systems in airgapped or restricted environments;
• Background in defense, aerospace, or complex enterprise systems;
• Familiarity with MBSE / SysML tooling and model-based data (XMI, Cameo, etc.);
• Experience with document parsing pipelines (Docling, Unstructured, etc.);
• Experience with orchestration tools (Airflow, Dagster, Prefect).
  
   

We offer:

• Four-month full-time contract engagement;
• Remote work with overlap in US business hours;
• High-impact project with direct influence on production AI systems;
• Close collaboration with client’s product and engineering teams;
• Opportunity to build core infrastructure for real-world AI applications — not prototypes.

You'll own how Empat delivers for its biggest, most complex clients — the accounts with layered approval chains, procurement and security reviews, and negotiations that unfold over months, not days. This role is ownership and building: you run key accounts end-to-end, and you build the enterprise-delivery muscle — governance, documentation, tender responses — that lets Empat win and keep bigger clients. You set the standards, build the toolkit, and personally run the accounts that matter most. If you think in systems, thrive in high-stakes stakeholder environments, and know how to make delivery feel predictable even when the client doesn't, this is for you.

Your responsibilities will include:

• Enterprise account ownership — own a book of key/enterprise accounts end-to-end: on-time delivery, project GPM, utilization, no delivery-caused billing slips.
• Delivery governance — set up and run the governance rhythm on your top accounts: steering cadence, status reporting, risk register, escalation paths — and make clients trust it.
• Delivery documentation & toolkit — build the reusable enterprise toolkit: SoW/MSA/change-request templates, an RFP/RFI response kit, a security/compliance answer pack.
• Procurement & tender cycles — carry formal procurement or tender cycles end-to-end, from first RFP to signed contract.
• Multi-stage negotiations — hold momentum through long, layered decision processes involving business, procurement, legal, security, and C-level stakeholders.
• Escalation ownership — be the go-to point when things get hard; resolve issues without eroding trust.
• Cross-functional collaboration — work closely with Sales, PMs, and Engineering to keep delivery synced with business goals and to grow your accounts.

• 3+ years in delivery management, account/program management, or client success in IT outsourcing/services.
• Proven experience running large corporate/enterprise accounts with many stakeholders and formal processes.
• A track record navigating procurement, legal, and compliance/security reviews — NDAs, DPAs, security questionnaires; awareness of ISO 27001 / SOC 2 / GDPR / HIPAA as relevant.
• Confidence with contract and delivery documentation — SoW, MSA, change management, formal reporting.
• Strong stakeholder management — able to present to and hold your own with C-level.
• English — Advanced (C1)+.
• Comfortable owning several accounts/projects simultaneously.

• Experience standing up delivery governance or a tender/proposal function from scratch.
• Delivery exposure to healthcare (HIPAA), fintech, or e-commerce.
• PMP, SAFe, PRINCE2, or ITIL certification.

• A company clients in 20+ countries trust — and a real mandate to build our enterprise delivery from the ground up.
• Projects and challenges that grow you as a specialist and a person.
• A team of creative, proactive, empathic people; regular feedback; no bureaucracy.
• Flexible, result-first schedule — a bright office in central Kyiv (Chykalenka str, with generator and battery backup) and work-from-home when you need it.
• Paid vacation, available right after the trial period.
• A 2-month trial period on average.
• Team traditions we actually enjoy — parties, picnics, and online activities.

• Brand voice & positioning — one consistent message and voice across every asset. You build the models: positioning, message house, tone of voice.
• Website content — audit and fix what exists, drive a new-pages plan, and ship conversion-minded pages.
• Blog, case studies & lead magnets — a repeatable, AI-powered content engine: ~6–8 articles/mo + case studies + lead-magnet content (e.g. AI workshops). You co-own lead-magnet strategy with the marketing lead.
• GEO / AI-search visibility — make empat.tech the answer inside ChatGPT, Perplexity, and AI Overviews. This is a headline outcome of the role.
• PR & thought leadership — narratives, pitches, press materials, and prep for podcast/media appearances. (Story-building, not community admin.)
• AI content systems — build the pipelines, prompt systems, and quality/tone-of-voice checks the whole team reuses.
• Google Business Profile — publish content and materials there as a distribution surface.

• Work at a Top-employer company (according to DOU 2025).
• A strong culture built on empathy, trust, openness, and real care for employees.
• Competitive compensation with regular reviews.
• Paid vacation and sick leave.
• Medical insurance.
• Personal learning budget and access to top HR tools, platforms, and practices.
• Team events and regular team-building activities.

• Project planning: developing plans and monitoring their execution;
• Financial forecasting and risk analysis;
• Communication with clients, managing their expectations and reporting;
• Building and coordinating the team's workflow;
• Tracking the workload and progress of team members;
• Creating and maintaining project documentation;
• Creating a positive communication atmosphere among all process participants;
• Managing several projects in parallel and switching between different contexts when needed;
• Working with different project formats, including in-house, outstaff, and support;
• Backlog formation, clear task definition, prioritisation, and task decomposition;
• Identifying opportunities to improve and automate project management processes;
• Using AI tools in daily work for documentation, reporting, meeting summaries, task structuring, risk analysis, and process optimisation.
  
  

• 3+ years of experience in IT project management;
• Understanding of Scrum and Kanban methodologies;
• Experience working with Mobile Apps, CMS systems, web platforms, preferably also: marketplaces, e-commerce, or other digital products;
• Strong knowledge of management and communication tools: Slack, Notion, Jira, Confluence;
• Experience managing remote project teams of more than 5 people;
• Strong ownership, leadership, and decision-making abilities;
• Proactive approach to identifying and addressing project issues;
• Ability to work effectively under pressure and meet deadlines;
• Readiness to work in a dynamic environment with multiple projects and frequent context switching;
• Comfort with different project types, including in-house and outstaff formats;
• Practical experience with AI tools or strong interest in using AI in daily project management work; we are using on corporate level Claude.ai, Claude Cowork;
• Ability to automate routine processes and look for more efficient ways of working;
• Empathy, ability to understand the team's dynamics, and provide constructive feedback;
• Upper-Intermediate / Advanced English proficiency;
• BA & Technical background is a big plus.

• Interesting projects and challenges that will ensure your development as a specialist and as a person and also the acceleration of our victory;
• Work in a team of creative, proactive and empathic people;
• Full working day with a flexible and animated schedule for you, because the main focus is the result, not the time or place;
• A comfortable, stylish and sunny office with a view of the city center (Chykalenka str) and the opportunity to work at home when you feel not so full of beans or just moody or lazy (with a generator and battery installation );
• Lack of bureaucracy, regular feedback and support from colleagues;
• Equal salary;
• Trial period (3 months on average, but everything is in your hands, so go ahead!);
• Fun parties, online-activity, picnics and more.

The company is building the control layer for an energy-constrained world — deploying AI, machine learning, and reinforcement learning to optimize HVAC systems, industrial equipment, and large-scale energy loads across commercial buildings, factories, hospitals, and data centers. The focus is on real, measurable impact: autonomous control systems that drive 20–30%+ energy savings in production environments.

We're looking for a BMS Control Engineer / Forward Deployment Engineer (TPM) who will join the team. This is a hands-on role for someone who doesn't just design building automation systems, but has deployed, commissioned, and optimized them in real-world infrastructure.

This role is for someone who takes full ownership of field deployments — from site discovery to production rollout. You'll work at the intersection of BMS/BAS systems, HVAC controls, and AI-driven optimization, deploying autonomous control systems across commercial buildings, factories, hospitals, and data centers.

Your responsibilities will include:

• Own deployments end-to-end: site discovery, integration, commissioning, validation, and rollout;
• Install, configure, and commission BAS/BMS and PLC-integrated systems;
• Deploy gateways, sensors, submeters, and communications infrastructure;
• Perform startup, point-to-point testing, and controls validation;
• Interface with AHUs, RTUs, chillers, boilers, pumps, cooling towers, and VFDs;
• Integrate through BACnet (IP & MS/TP), Modbus, LON, and IP networks;
• Work with Niagara, Siemens, Honeywell, Johnson Controls Metasys, Delta, and other BAS platforms;
• Configure addressing, routing, communications, and device connectivity;
• Diagnose controls hardware, wiring, networking, protocol, and sensor issues;
• Support deployment of AI-driven and RL-driven control strategies;
• Own deployment schedules, communications, milestones, and execution;
• Coordinate customers, contractors, vendors, and internal engineering teams;
• Maintain deployment plans, commissioning reports, diagrams, and as-built documentation.

• Degree in Electrical Engineering, Mechanical Engineering, HVAC, or related discipline — or equivalent BAS/PLC/SCADA/DCIM experience;
• 2+ years of hands-on BACnet experience (IP & MS/TP);
• 2+ years of Modbus experience;
• 2+ years of HVAC Controls / DDC / BMS experience;
• Strong understanding of BMS/DDC systems, PLCs, PID loops, hydronics, and refrigeration;
• Experience with BAS platforms: Niagara (Tridium), Siemens, Honeywell, Johnson Controls Metasys, Delta;
• Hands-on commissioning and troubleshooting experience in the field;
• Ability to work independently and take ownership in customer-facing environments.

• Niagara (Tridium), EPA 608, NATE, or OSHA certifications;
• Experience in industrial facilities, healthcare, mission-critical environments, or data centers;
• Exposure to IoT, edge computing, SCADA, or DCIM platforms;
• Experience with LON protocol and IP networking in BAS contexts.

• Full-time engagement on a high-impact infrastructure project;
• Remote-friendly with on-site deployment work at client facilities;
• Direct work with cutting-edge AI and reinforcement learning applied to real-world systems;
• Measurable impact — 20–30%+ energy savings across live deployments;
• Opportunity to help define the future of autonomous building and industrial control systems.

We are looking for a Senior Full-Stack Developer (AI-Native) to join the project full-time. This person will own the full stack — backend, frontend, and AI/agent layer — with no splitting between projects. They need to be a thinking partner, not an executor — someone the client's technical leadership wants to work with directly.

Your responsibilities will include:

• Own the full stack end-to-end — backend, frontend, and AI/agent layer — architecture decisions, performance work, integration, testing — without hand-holding.
• Work directly with the client's technical leadership as a thinking partner.
• Build and maintain LLM-powered agent systems with observability, evaluation, and structured tracing.
• Cover backend, frontend, and infrastructure independently — no "that's not my area."
• Use AI-assisted development (Claude Code or equivalent) fluently and extensively as a primary tool.

What we expect from you:

Core stack — Backend:

• Python — FastAPI, SQLAlchemy, Alembic.
• PostgreSQL + PostGIS — spatial data modelling, multi-tenant isolation at the database, session, and repository layers.
• Redis — async task queues.
• Unit & integration tests — Pytest.

Core stack — Frontend:

• React + TypeScript — strict typing; comfortable with generics, discriminated unions, and type inference.
• Next.js — App Router, Server Components, server-side data fetching, middleware, Server Actions.
• Zustand — store design, selectors, SSR hydration concerns.
• Unit & integration tests + E2E — Vitest, Cypress or equivalent.

AI / Agent Layer:

• LLM-powered agents — SSE, tool-use patterns, prompt engineering.
• Observability & evaluation — structured tracing of agent runs and tool calls, usage tracking, analytics.

Infrastructure:

• AWS — ECS, S3, containerized deploys.
• Terraform — infrastructure as code.
• CI/CD — GitHub Actions.

Engineering Practices:

• Static typing — Pyright as CI gate; type hints on every signature, no escape hatches.
• Multi-tenancy — tenant isolation at the database, session, and repository layers.
• Git discipline — conventional commits, granular atomic history, clean PRs.

Tooling — AI-assisted development (Claude Code):

AI is a primary, everyday tool on this project, not an occasional helper. We expect a candidate who has moved well beyond ad-hoc prompting and treats their AI setup as part of their engineering craft.

• AI-native development — non-negotiable. Daily, extensive, fluent use of Claude Code (or equivalent) for reading, writing, refactoring, debugging, and navigating a large codebase. Working without AI in the loop is not how this team operates.
• Plain prompting is not enough. "Ask ChatGPT a question and paste the answer" is the baseline we expect candidates to be past. We're looking for someone who engineers their AI workflow: rich structured context, project conventions and reference examples fed to the model, clear scoping, iteration, and rigorous review of generated output.
• Skills, Hooks, Subagents— must understand, must be able to build, and already uses in real work. The candidate should be able to clearly explain what each is, and — critically — has already created and uses them day-to-day, not just heard of them:
  • Skills — reusable, on-demand instruction/knowledge packages that extend the agent's competence for a given task type (e.g. scaffold a module, generate a PR, run a review) and encode the team's conventions.
  • Hooks — deterministic, automated triggers on lifecycle events (pre-commit, before/after edit, on stop, etc.) executed by the harness itself — e.g. auto-running lint/typecheck/tests on changed files, or guarding protected areas.
  • Subagents — delegating multi-step or parallel work (large refactors, audits, codebase research) to scoped agents, with verification of their output.
• MCP awareness — understands the Model Context Protocol and how to connect AI to real context and tools (codebase, Git, issue tracker, browser, observability) rather than working blind. Hands-on MCP usage is a strong plus.
• Structured change management — artifact-driven workflow from exploration through implementation to verification.
• Critical, not credulous — reviews everything the model produces, never commits code they don't understand, knows where AI accelerates the work (boilerplate, tests, scaffolding, exploration) and where it does not (complex domain/architecture logic). AI is a force multiplier for their own thinking, never a copy-paste crutch.

Soft skills / Mindset:

• Initiative — proactively asks questions, proposes solutions, flags issues without being asked.
• Software Engineering Mindset — understands fundamentals, not just framework recipes; can reason about problems from first principles.
• Comfortable with the unknown — says "I don't know, let me find out," explores and digs in.
• Thinks aloud — communicates where they are, what they're considering, what they're unsure about.
• Fast — moves quickly without sacrificing quality; comfortable with startup pace and shifting priorities.
• Collaborative but opinionated — contributes ideas, challenges assumptions respectfully.
• English — B2+ — daily verbal and written communication with the client and their team; working proficiency minimum.

What We Offer:

• Work at a Top-employer company (according to DOU 2025).
• A strong culture built on empathy, trust, openness, and real care for employees.
• Competitive compensation with regular reviews.
• Paid vacation and sick leave.
• Medical insurance.
• Personal learning budget and access to top HR tools, platforms, and practices.
• Team events and regular team-building activities.
• Flexible hybrid work model with an office in central Kyiv.