KaaIoT

Requirements:

• 1–3 years of commercial development experience;
• Strong knowledge of JavaScript and TypeScript;
• Experience with Node.js and/or Bun.js;
• Experience with Vue.js is preferred; React is also acceptable;
• Good understanding of full-stack web application development;
• Understanding of WebSockets and real-time communication;
• Experience working with PostgreSQL;
• Good understanding of asynchronous programming;
• Confident working with the Git version control system;
• Strong analytical and problem-solving skills;

• Intermediate level of English.

   

Would be a plus:

• Experience with modern backend architecture and API design;
• Experience working with ORMs or query builders;
• Familiarity with deployment, CI/CD, and cloud environments;
• Experience building scalable products or SaaS platforms.

• Experience using AI tools for coding to improve productivity;

   

Responsibilities:

• Develop and maintain full-stack product features with attention to quality and performance;
• Participate in end-to-end development, from idea to production;
• Build both backend and frontend parts of the application;
• Work with real-time features using WebSockets;
• Deliver features quickly and efficiently;

About the company

Our client is a leading autonomous vehicle technology company operating at the cutting edge of self-driving software development. 

Role overview

We are not looking for a traditional SOC analyst. This role is about building detection systems, not clicking through alerts. You will work with large volumes of logs (cloud, application, network), design detection logic, and improve it over time. That includes both rule-based detection (SIEM/XDR) and data-driven approaches (statistical models, anomaly detection, simple ML where it makes sense). You should be comfortable treating logs as a data problem, not just a monitoring stream.

Important! This is not a role where you:

• sit in SIEM all day clicking alerts
• blindly add rules
• overcomplicate things with ML

This is a role where you: build detection systems that work in practice.

What you'll be doing

Detection & analytics

• Build and maintain detections across:
• application logs (auth, APIs, business logic abuse)
• cloud activity (CloudTrail, IAM, infrastructure changes)
• network telemetry (DNS, proxy, firewall, NetFlow)
• Work directly with data in platforms like Elasticsearch / Splunk / similar
• Write and tune detection logic (queries, correlation rules)
• Reduce noise — expect to spend time fixing false positives, not just adding new rules.

Working with data (this is a big part of the job)

• Build pipelines for:
• log ingestion
• normalization
• feature extraction
• Work with streaming or batch pipelines (Kafka / queues / scheduled jobs)
• Turn raw logs (e.g. CloudTrail) into structured data usable for detection.

Anomaly detection / ML (practical, not theoretical)

• Apply simple models where they add value (e.g. One-Class SVM or similar approaches)
• Focus on:
• behavior baselining
• anomaly scoring
• Tune models based on real output (false positives matter more than theory) 
• If ML does not improve signal — don't use it.

Automation & response

• Build response playbooks for common cases
• Automate where it actually saves time (not for the sake of it)
• Integrate with SOAR or write lightweight orchestration
• Improve:
• detection speed
• response consistency.

AI usage (realistic expectations)

• Use LLMs for:
• alert enrichment
• investigation summaries
• internal tooling
• Not building an "AI security platform"
• Focus on practical gains, not hype.

Threat hunting

• Run targeted hunts based on hypotheses
• Use internal data + external signals
• Identify gaps in logging and detection.

Requirements

• Solid experience with SIEM (Elastic, Splunk, Sentinel, etc.)
• Strong understanding of:
• cloud activity (especially AWS logs and IAM)
• network basics
• modern application behavior (APIs, auth flows)
• Comfortable working with large datasets (not afraid of raw logs)
• Python or similar for data processing
• Experience with automation (SOAR or custom scripts).

Nice-to-have (but not critical)

• Experience applying ML to logs (even simple models is enough)
• Familiarity with LLMs in tooling (not research)
• Experience with data pipelines (Kafka, Spark, etc.)
• MITRE ATT&CK mapping

What will make you effective here

• You don't trust alerts blindly
• You care about signal quality, not number of detections
• You can debug why a detection is noisy or useless
• You understand systems, not just tools
• You prefer building something once instead of repeating manual work.

How success looks like

• Fewer false positives
• Better visibility across systems
• Faster investigations
• Less manual work in SOC
• Detections that actually catch real issues

About the company

Our client is a leading autonomous vehicle technology company operating at the cutting edge of self-driving software development. 

Role overview

We are not looking for a traditional SOC analyst. This role is about building detection systems, not clicking through alerts. You will work with large volumes of logs (cloud, application, network), design detection logic, and improve it over time. That includes both rule-based detection (SIEM/XDR) and data-driven approaches (statistical models, anomaly detection, simple ML where it makes sense). You should be comfortable treating logs as a data problem, not just a monitoring stream.

Important! This is not a role where you:

• sit in SIEM all day clicking alerts
• blindly add rules
• overcomplicate things with ML

This is a role where you: build detection systems that work in practice.

What you'll be doing

Detection & analytics

• Build and maintain detections across:
• application logs (auth, APIs, business logic abuse)
• cloud activity (CloudTrail, IAM, infrastructure changes)
• network telemetry (DNS, proxy, firewall, NetFlow)
• Work directly with data in platforms like Elasticsearch / Splunk / similar
• Write and tune detection logic (queries, correlation rules)
• Reduce noise — expect to spend time fixing false positives, not just adding new rules.

Working with data (this is a big part of the job)

• Build pipelines for:
• log ingestion
• normalization
• feature extraction
• Work with streaming or batch pipelines (Kafka / queues / scheduled jobs)
• Turn raw logs (e.g. CloudTrail) into structured data usable for detection.

Anomaly detection / ML (practical, not theoretical)

• Apply simple models where they add value (e.g. One-Class SVM or similar approaches)
• Focus on:
• behavior baselining
• anomaly scoring
• Tune models based on real output (false positives matter more than theory) 
• If ML does not improve signal — don't use it.

Automation & response

• Build response playbooks for common cases
• Automate where it actually saves time (not for the sake of it)
• Integrate with SOAR or write lightweight orchestration
• Improve:
• detection speed
• response consistency.

AI usage (realistic expectations)

• Use LLMs for:
• alert enrichment
• investigation summaries
• internal tooling
• Not building an "AI security platform"
• Focus on practical gains, not hype.

Threat hunting

• Run targeted hunts based on hypotheses
• Use internal data + external signals
• Identify gaps in logging and detection.

Requirements

• Solid experience with SIEM (Elastic, Splunk, Sentinel, etc.)
• Strong understanding of:
• cloud activity (especially AWS logs and IAM)
• network basics
• modern application behavior (APIs, auth flows)
• Comfortable working with large datasets (not afraid of raw logs)
• Python or similar for data processing
• Experience with automation (SOAR or custom scripts).

Nice-to-have (but not critical)

• Experience applying ML to logs (even simple models is enough)
• Familiarity with LLMs in tooling (not research)
• Experience with data pipelines (Kafka, Spark, etc.)
• MITRE ATT&CK mapping

What will make you effective here

• You don't trust alerts blindly
• You care about signal quality, not number of detections
• You can debug why a detection is noisy or useless
• You understand systems, not just tools
• You prefer building something once instead of repeating manual work.

How success looks like

• Fewer false positives
• Better visibility across systems
• Faster investigations
• Less manual work in SOC
• Detections that actually catch real issues

Requirements:

• 1+ years of experience in development
• Strong knowledge of Javascript and TypeScript
• Strong knowledge of Angular
• Strong analytical and problem-solving skills
• Experience working with RxJS ,NgRx ,signals, and new angular syntax template
• Confident AI prompting, understanding of LLM principles (Context window, RAG, System prompts)
• Experience working with AI coding assistants (Cursor, Claude Code, GitHub Copilot)
• Good understanding of asynchronous and reactive programming
• Confident working with the Git version control system
• Understanding of GraphQL
• Intermediate level of English

Would be a plus:

• Experience working with React
• Experience working with Websockets
• Experience building large-scale SaaS platforms supporting millions of users.

Responsibilities:

• Build features and systems with attention to detail and performance.
• Own end-to-end development, from conception to production.
• Engineer not only solutions but also tools to understand the problem.
• Work closely with cross-functional stakeholders to deliver a world-class product.
• Identify and implement improvements to our existing systems.

About the project:

Project management platform. With the help of own API, it’s possible to do multiple integrations with communication, sales, analytics and other applications that are used by co-workers on a daily basis.

We are looking for a frontend engineer to improve the beautifully crafted product that helps millions of people to enjoy their remote work! You will be responsible to deliver production-ready functionality in a cross-functional team and will be able to reach millions of people with your best effort and working time as part of a multinational team of highly skilled developers.

• 1+ years of experience in development
• Strong knowledge of Javascript and TypeScript
• Strong knowledge of Angular
• Strong analytical and problem-solving skills
• Experience working with RxJS ,NgRx ,signals, and new angular syntax template
• Confident AI prompting, understanding of LLM principles (Context window, RAG, System prompts)
• Experience working with AI coding assistants (Cursor, Claude Code, GitHub Copilot)
• Good understanding of asynchronous and reactive programming
• Confident working with the Git version control system
• Understanding of GraphQL

• Intermediate level of English

   

Would be a plus:

• Experience working with React
• Experience working with Websockets

• Experience building large-scale SaaS platforms supporting millions of users.

   

Responsibilities:

• Build features and systems with attention to detail and performance.
• Own end-to-end development, from conception to production.
• Engineer not only solutions but also tools to understand the problem.
• Work closely with cross-functional stakeholders to deliver a world-class product.

• Identify and implement improvements to our existing systems.

   

About the project:

Project management platform. With the help of own API, it’s possible to do multiple integrations with communication, sales, analytics and other applications that are used by co-workers on a daily basis.

We are looking for a frontend engineer to improve the beautifully crafted product that helps millions of people to enjoy their remote work! You will be responsible to deliver production-ready functionality in a cross-functional team and will be able to reach millions of people with your best effort and working time as part of a multinational team of highly skilled developers.

Location: Remote

Team: Security / Platform

About the company

Our client is a leading autonomous vehicle technology company operating at the cutting edge of self-driving software development. 

Role overview

We are not looking for a traditional SOC analyst. This role is about building detection systems, not clicking through alerts. You will work with large volumes of logs (cloud, application, network), design detection logic, and improve it over time. That includes both rule-based detection (SIEM/XDR) and data-driven approaches (statistical models, anomaly detection, simple ML where it makes sense). You should be comfortable treating logs as a data problem, not just a monitoring stream.

Important! This is not a role where you:

• sit in SIEM all day clicking alerts
• blindly add rules
• overcomplicate things with ML

This is a role where you: build detection systems that work in practice.

What you'll be doing

Detection & analytics

• Build and maintain detections across:
• application logs (auth, APIs, business logic abuse)
• cloud activity (CloudTrail, IAM, infrastructure changes)
• network telemetry (DNS, proxy, firewall, NetFlow)
• Work directly with data in platforms like Elasticsearch / Splunk / similar
• Write and tune detection logic (queries, correlation rules)
• Reduce noise — expect to spend time fixing false positives, not just adding new rules.

Working with data (this is a big part of the job)

• Build pipelines for:
• log ingestion
• normalization
• feature extraction
• Work with streaming or batch pipelines (Kafka / queues / scheduled jobs)
• Turn raw logs (e.g. CloudTrail) into structured data usable for detection.

Anomaly detection / ML (practical, not theoretical)

• Apply simple models where they add value (e.g. One-Class SVM or similar approaches)
• Focus on:
• behavior baselining
• anomaly scoring
• Tune models based on real output (false positives matter more than theory) 
• If ML does not improve signal — don't use it.

Automation & response

• Build response playbooks for common cases
• Automate where it actually saves time (not for the sake of it)
• Integrate with SOAR or write lightweight orchestration
• Improve:
• detection speed
• response consistency.

AI usage (realistic expectations)

• Use LLMs for:
• alert enrichment
• investigation summaries
• internal tooling
• Not building an "AI security platform"
• Focus on practical gains, not hype.

Threat hunting

• Run targeted hunts based on hypotheses
• Use internal data + external signals

• Identify gaps in logging and detection.

   

Requirements

• Solid experience with SIEM (Elastic, Splunk, Sentinel, etc.)
• Strong understanding of:
• cloud activity (especially AWS logs and IAM)
• network basics
• modern application behavior (APIs, auth flows)
• Comfortable working with large datasets (not afraid of raw logs)
• Python or similar for data processing

• Experience with automation (SOAR or custom scripts).

   

Nice-to-have (but not critical)

• Experience applying ML to logs (even simple models is enough)
• Familiarity with LLMs in tooling (not research)
• Experience with data pipelines (Kafka, Spark, etc.)

• MITRE ATT&CK mapping

   

What will make you effective here

• You don't trust alerts blindly
• You care about signal quality, not number of detections
• You can debug why a detection is noisy or useless
• You understand systems, not just tools

• You prefer building something once instead of repeating manual work.

   

How success looks like

• Fewer false positives
• Better visibility across systems
• Faster investigations
• Less manual work in SOC
• Detections that actually catch real issues

Requirements:

• 1–3 years of commercial development experience;
• Strong knowledge of JavaScript and TypeScript;
• Experience with Node.js and/or Bun.js;
• Experience with Vue.js is preferred; React is also acceptable;
• Good understanding of full-stack web application development;
• Understanding of WebSockets and real-time communication;
• Experience working with PostgreSQL;
• Good understanding of asynchronous programming;
• Confident working with the Git version control system;
• Strong analytical and problem-solving skills;
• Intermediate level of English.

Would be a plus:

• Experience with modern backend architecture and API design;
• Experience working with ORMs or query builders;
• Familiarity with deployment, CI/CD, and cloud environments;
• Experience building scalable products or SaaS platforms.
• Experience using AI tools for coding to improve productivity;

Responsibilities:

• Develop and maintain full-stack product features with attention to quality and performance;
• Participate in end-to-end development, from idea to production;
• Build both backend and frontend parts of the application;
• Work with real-time features using WebSockets;
• Deliver features quickly and efficiently.

About the company

Our client is a leading autonomous vehicle technology company operating at the cutting edge of self-driving software development. 

Role overview

We are not looking for a traditional SOC analyst. This role is about building detection systems, not clicking through alerts. You will work with large volumes of logs (cloud, application, network), design detection logic, and improve it over time. That includes both rule-based detection (SIEM/XDR) and data-driven approaches (statistical models, anomaly detection, simple ML where it makes sense). You should be comfortable treating logs as a data problem, not just a monitoring stream.

Important! This is not a role where you:

• sit in SIEM all day clicking alerts
• blindly add rules
• overcomplicate things with ML

This is a role where you: build detection systems that work in practice.

What you'll be doing

Detection & analytics

• Build and maintain detections across:
• application logs (auth, APIs, business logic abuse)
• cloud activity (CloudTrail, IAM, infrastructure changes)
• network telemetry (DNS, proxy, firewall, NetFlow)
• Work directly with data in platforms like Elasticsearch / Splunk / similar
• Write and tune detection logic (queries, correlation rules)
• Reduce noise — expect to spend time fixing false positives, not just adding new rules.

Working with data (this is a big part of the job)

• Build pipelines for:
• log ingestion
• normalization
• feature extraction
• Work with streaming or batch pipelines (Kafka / queues / scheduled jobs)
• Turn raw logs (e.g. CloudTrail) into structured data usable for detection.

Anomaly detection / ML (practical, not theoretical)

• Apply simple models where they add value (e.g. One-Class SVM or similar approaches)
• Focus on:
• behavior baselining
• anomaly scoring
• Tune models based on real output (false positives matter more than theory) 
• If ML does not improve signal — don't use it.

Automation & response

• Build response playbooks for common cases
• Automate where it actually saves time (not for the sake of it)
• Integrate with SOAR or write lightweight orchestration
• Improve:
• detection speed
• response consistency.

AI usage (realistic expectations)

• Use LLMs for:
• alert enrichment
• investigation summaries
• internal tooling
• Not building an "AI security platform"
• Focus on practical gains, not hype.

Threat hunting

• Run targeted hunts based on hypotheses
• Use internal data + external signals
• Identify gaps in logging and detection.

Requirements

• Solid experience with SIEM (Elastic, Splunk, Sentinel, etc.)
• Strong understanding of:
• cloud activity (especially AWS logs and IAM)
• network basics
• modern application behavior (APIs, auth flows)
• Comfortable working with large datasets (not afraid of raw logs)
• Python or similar for data processing
• Experience with automation (SOAR or custom scripts).

Nice-to-have (but not critical)

• Experience applying ML to logs (even simple models is enough)
• Familiarity with LLMs in tooling (not research)
• Experience with data pipelines (Kafka, Spark, etc.)
• MITRE ATT&CK mapping

What will make you effective here

• You don't trust alerts blindly
• You care about signal quality, not number of detections
• You can debug why a detection is noisy or useless
• You understand systems, not just tools
• You prefer building something once instead of repeating manual work.

How success looks like

• Fewer false positives
• Better visibility across systems
• Faster investigations
• Less manual work in SOC
• Detections that actually catch real issues

About the Role:

We are looking for a firmware engineer who really knows how to work with modern hardware (ESP32-S3, PICAD-compatible boards) and Zephyr OS. The main task is to write stable, production-ready code for IoT devices of the "data logger / gateway" level: sensors, Modbus, LTE/Wi-Fi, OTA, local logic, energy saving.

No academic R&D — you need a person who quickly makes a working product.

Responsibilities:

• Development of firmware for Zephyr OS for ESP32-S3 / ESP32-C6;
• Work with PICAD-compatible peripherals (sensors, interfaces, IO);
• Implementation of protocols: Modbus RTU/TCP, UART, RS-485, SPI, I2C;
• Network stack settings: Wi-Fi, LTE (via external modules), MQTT;
• OTA updates (MCUboot, Zephyr samples, custom schematics);
• Data buffering, local storage, fallback modes;
• Integration with backend API (REST/MQTT), queue/telemetry processing;
• Optimization of power consumption and performance;
• Writing unit-/integration-tests, working with hardware-bring-up.

Requirements:

• Deep experience in C/C++ firmware development;
• Commercial experience with Zephyr RTOS is required (device tree, Kconfig, drivers, subsystems);
• Practical experience with ESP32-S3 / ESP32-C3 / ESP32-C6;
• Understanding of MCUboot, partition layout, OTA-pipeline;
• Ability to work with peripherals: UART, SPI, I2C, PWM, ADC, RS-485;
• Experience with Modbus (master/slave), preferably with real devices;
• Debug experience: JTAG, OpenOCD, logic analyzer;
• Git, CI/CD, the ability to work in a normal product, and not "flash firmware".

Nice to have:

• BLE (Zephyr BT stack);
• Python for tooling (scripts, tests, production tools).

We Offer:

• Work on a real IoT product (energy logger / gateway), which is already in production;
• Opportunity for professional growth and career development;
• Vacation — 18 working days per year;
• Friendly working environment;
• Sick leave — 5 working days (without documents);
• Health insurance.

Requirements:

• 1–3 years of commercial development experience;
• Strong knowledge of JavaScript and TypeScript;
• Experience with Node.js and/or Bun.js;
• Experience with Vue.js is preferred; React is also acceptable;
• Good understanding of full-stack web application development;
• Understanding of WebSockets and real-time communication;
• Experience working with PostgreSQL;
• Good understanding of asynchronous programming;
• Confident working with the Git version control system;
• Strong analytical and problem-solving skills;
• Intermediate level of English.

Would be a plus:

• Experience with modern backend architecture and API design;
• Experience working with ORMs or query builders;
• Familiarity with deployment, CI/CD, and cloud environments;
• Experience building scalable products or SaaS platforms.
• Experience using AI tools for coding to improve productivity;

Responsibilities:

• Develop and maintain full-stack product features with attention to quality and performance;
• Participate in end-to-end development, from idea to production;
• Build both backend and frontend parts of the application;
• Work with real-time features using WebSockets;
• Deliver features quickly and efficiently;

Requirements:

• 1+ years of experience in development
• Strong knowledge of Javascript and TypeScript
• Strong knowledge of Angular
• Strong analytical and problem-solving skills
• Experience working with RxJS ,NgRx ,signals, and new angular syntax template
• Confident AI prompting, understanding of LLM principles (Context window, RAG, System prompts)
• Experience working with AI coding assistants (Cursor, Claude Code, GitHub Copilot)
• Good understanding of asynchronous and reactive programming
• Confident working with the Git version control system
• Understanding of GraphQL
• Intermediate level of English

Would be a plus:

• Experience working with React
• Experience working with Websockets
• Experience building large-scale SaaS platforms supporting millions of users.

Responsibilities:

• Build features and systems with attention to detail and performance.
• Own end-to-end development, from conception to production.
• Engineer not only solutions but also tools to understand the problem.
• Work closely with cross-functional stakeholders to deliver a world-class product.
• Identify and implement improvements to our existing systems.

About the project:

Project management platform. With the help of own API, it’s possible to do multiple integrations with communication, sales, analytics and other applications that are used by co-workers on a daily basis.

We are looking for a frontend engineer to improve the beautifully crafted product that helps millions of people to enjoy their remote work! You will be responsible to deliver production-ready functionality in a cross-functional team and will be able to reach millions of people with your best effort and working time as part of a multinational team of highly skilled developers.

Requirements:

• 1–3 years of commercial development experience;
• Strong knowledge of JavaScript and TypeScript;
• Experience with Node.js and/or Bun.js;
• Experience with Vue.js is preferred; React is also acceptable;
• Good understanding of full-stack web application development;
• Understanding of WebSockets and real-time communication;
• Experience working with PostgreSQL;
• Good understanding of asynchronous programming;
• Confident working with the Git version control system;
• Strong analytical and problem-solving skills;
• Intermediate level of English.

Would be a plus:

• Experience with modern backend architecture and API design;
• Experience working with ORMs or query builders;
• Familiarity with deployment, CI/CD, and cloud environments;
• Experience building scalable products or SaaS platforms.
• Experience using AI tools for coding to improve productivity.

Responsibilities:

• Develop and maintain full-stack product features with attention to quality and performance;
• Participate in end-to-end development, from idea to production;
• Build both backend and frontend parts of the application;
• Work with real-time features using WebSockets;
• Deliver features quickly and efficiently.

Requirements:

• 1+ years of experience in development
• Strong knowledge of Javascript and TypeScript
• Strong knowledge of Angular
• Strong analytical and problem-solving skills
• Experience working with RxJS ,NgRx ,signals, and new angular syntax template
• Confident AI prompting, understanding of LLM principles (Context window, RAG, System prompts)
• Experience working with AI coding assistants (Cursor, Claude Code, GitHub Copilot)
• Good understanding of asynchronous and reactive programming
• Confident working with the Git version control system
• Understanding of GraphQL
• Upper-Intermediate level of English

Would be a plus:

• Experience working with React
• Experience working with WebSockets
• Experience building large-scale SaaS platforms supporting millions of users

Responsibilities:

• Build features and systems with attention to detail and performance.
• Own end-to-end development, from conception to production.
• Engineer not only solutions but also tools to understand the problem.
• Work closely with cross-functional stakeholders to deliver a world-class product.
• Identify and implement improvements to our existing systems.

About the project:

Project management platform. With the help of own API, it’s possible to do multiple integrations with communication, sales, analytics and other applications that are used by co-workers on a daily basis.

We are looking for a frontend engineer to improve the beautifully crafted product that helps millions of people to enjoy their remote work! You will be responsible to deliver production-ready functionality in a cross-functional team and will be able to reach millions of people with your best effort and working time as part of a multinational team of highly skilled developers.

About the Role:

Ми шукаємо інженера прошивок, який реально вміє працювати з сучасним залізом (ESP32-S3, PICAD-сумісні плати) та Zephyr OS. Основне завдання — писати стійкий, production-ready код для IoT-пристроїв рівня “data logger / gateway”: сенсори, Modbus, LTE/Wi-Fi, OTA, локальна логіка, енергозбереження.

Жодного академічного R&D — потрібна людина, яка швидко робить робочий продукт.

Responsibilities:

• Розробка firmware під Zephyr OS для ESP32-S3 / ESP32-C6;
• Робота з PICAD-сумісною периферією (датчики, інтерфейси, IO);
• Реалізація протоколів: Modbus RTU/TCP, UART, RS-485, SPI, I2C;
• Налаштування мережевих стеків: Wi-Fi, LTE (через зовнішні модулі), MQTT;
• OTA-оновлення (MCUboot, зразки Zephyr, кастомні схеми);
• Буферизація даних, локальний storage, fallback-режими;
• Інтеграція з backend API (REST/MQTT), обробка queue/telemetry;
• Оптимізація енергоспоживання та продуктивності;
• Написання unit-/integration-tests, робота з hardware-bring-up.

Requirements:

• Глибокий досвід розробки прошивок на C/C++;
• Комерційний досвід із Zephyr RTOS обов’язковий (device tree, Kconfig, drivers, subsystems);
• Практичний досвід роботи з ESP32-S3 / ESP32-C3 / ESP32-C6;
• Розуміння MCUboot, partition layout, OTA-pipeline;
• Уміння працювати з периферією: UART, SPI, I2C, PWM, ADC, RS-485;
• Досвід роботи з Modbus (master/slave), бажано з реальними пристроями;
• Досвід дебагу: JTAG, OpenOCD, logic analyzer;
• Git, CI/CD, уміння працювати в нормальному продукті, а не «прошивка нашвидкуруч».

Nice to have:

• BLE (Zephyr BT stack);
• Python для tooling (скрипти, тести, виробничі тулзи).

We Offer:

• Робота над реальним IoT-продуктом (energy logger / gateway), який уже йде у виробництво;
• Можливість професійного зростання та кар’єрного розвитку;
• Відпустка — 18 робочих днів на рік;
• Дружнє робоче середовище;
• Лікарняний — 5 робочих днів (без документів);
• Медичне страхування.

About the Role:

Ми шукаємо інженера прошивок, який реально вміє працювати з сучасним залізом (ESP32-S3, PICAD-сумісні плати) та Zephyr OS. Основне завдання — писати стійкий, production-ready код для IoT-пристроїв рівня “data logger / gateway”: сенсори, Modbus, LTE/Wi-Fi, OTA, локальна логіка, енергозбереження.

Жодного академічного R&D — потрібна людина, яка швидко робить робочий продукт.

Responsibilities:

• Розробка firmware під Zephyr OS для ESP32-S3 / ESP32-C6;
• Робота з PICAD-сумісною периферією (датчики, інтерфейси, IO);
• Реалізація протоколів: Modbus RTU/TCP, UART, RS-485, SPI, I2C;
• Налаштування мережевих стеків: Wi-Fi, LTE (через зовнішні модулі), MQTT;
• OTA-оновлення (MCUboot, зразки Zephyr, кастомні схеми);
• Буферизація даних, локальний storage, fallback-режими;
• Інтеграція з backend API (REST/MQTT), обробка queue/telemetry;
• Оптимізація енергоспоживання та продуктивності;
• Написання unit-/integration-tests, робота з hardware-bring-up.

Requirements:

• Глибокий досвід розробки прошивок на C/C++;
• Комерційний досвід із Zephyr RTOS обов’язковий (device tree, Kconfig, drivers, subsystems);
• Практичний досвід роботи з ESP32-S3 / ESP32-C3 / ESP32-C6;
• Розуміння MCUboot, partition layout, OTA-pipeline;
• Уміння працювати з периферією: UART, SPI, I2C, PWM, ADC, RS-485;
• Досвід роботи з Modbus (master/slave), бажано з реальними пристроями;
• Досвід дебагу: JTAG, OpenOCD, logic analyzer;
• Git, CI/CD, уміння працювати в нормальному продукті, а не «прошивка нашвидкуруч».

Nice to have:

• BLE (Zephyr BT stack);
• Python для tooling (скрипти, тести, виробничі тулзи).

We Offer:

• Робота над реальним IoT-продуктом (energy logger / gateway), який уже йде у виробництво;
• Можливість професійного зростання та кар’єрного розвитку;
• Відпустка — 18 робочих днів на рік;
• Дружнє робоче середовище;
• Лікарняний — 5 робочих днів (без документів);
• Медичне страхування.