IoT Engineer

• Design and implement scalable IoT solutions from sensor to cloud, ensuring seamless integration between

vehicle hardware (fuel sensors, GPS trackers, OBD devices) and the Anytime Diesel platform

• Integrate industrial and automotive sensors, microcontrollers, and gateways with the platform

• Develop, optimize, and troubleshoot data flow using protocols such as CAN bus, Modbus, RS485, TCP, and

RTU

• Manage the full IoT device lifecycle across the fleet — provisioning, remote configuration, health monitoring,

and OTA/FOTA firmware updates

• Collaborate with software, data, and operations teams to define data models and ensure clean data ingestion for

fleet analytics

• Conduct testing, debugging, and performance analysis of embedded firmware and IoT systems using tools like

oscilloscopes and logic analyzers

• Create technical documentation — architecture diagrams, API specs, and deployment guides

Embedded Systems / Firmware Engineer

Key Responsibilities

• Develop embedded firmware for IoT and connected devices using C/C++.
• Work on RTOS, bare-metal programming, memory management, device drivers, and communication protocols.
• Develop and integrate drivers/interfaces for cameras, motors, sensors, and vision systems.
• Work with Python and Shell scripting for development and automation.
• Apply basic AI/ML and computer vision concepts to embedded applications.
• Collaborate on electrical and mechanical design, hardware integration, testing, and debugging.

Required Skills

• C, C++, Python, Shell Scripting
• Embedded Systems & Firmware
• IoT, RTOS, Bare Metal
• Memory Management & Device Drivers
• Communication Protocols
• Camera, Motor & Vision Systems
• Basic AI/ML understanding
• Electrical & Mechanical Design understanding

IoT Engineer – Telematics & C#/.NET

Experience :05+ Years

Location : Ahmedabad

ABOUT MYFMS

MyFMS is Micpoint B.V.'s SaaS platform for fleet, facility, and access management, built on .NET and C#, and hosted on our own private cloud in the Netherlands, spread across two data centers. A key part of MyFMS is its connector layer: the software that links telematics and IoT hardware in the field (such as GPS trackers and CAN-bus interfaces) to the platform. To further build out and standardize this layer, we're looking for an IoT Engineer with C#/.NET development experience.

WHAT YOU'LL DO

•    Implement and maintain telematics integrations in C#/.NET on MyFMS's connectors, which link telematics hardware (e.g. GPS trackers and CAN-bus interfaces) to the platform.

•    Investigate which configurations, protocol settings, and command sets of supported hardware (e.g. CAN/LVCAN parameters) can serve as a standard, and document them.

•    Research and manage firmware versions for telematics devices, and advise on firmware updates and compatibility.

•    Translate device-specific protocols into a uniform, reusable data structure within the platform.

•    Document device configurations and firmware standards in Markdown for the development team and support organization.

•    Work according to our DevOps way of working, integrating your work into the CI/CD pipelines we use for testing and releases.

•    Collaborate with the (international) development team on the architecture of the connector layer and contribute to the technical roadmap.

•    Support troubleshooting of field issues, such as connectivity or synchronization problems with hardware.

•    Build simulators for telematics hardware, so protocols, configurations, and firmware behavior can be tested without needing physical devices.

•    Use AI, and work with and train models, to build simulations and test setups.

•    Ensure the connector integrations are fully testable (including unit and integration tests), safeguarding the quality of the telematics integrations.

WHAT THE ROLE REQUIRES

•    Bachelor's/Master's level thinking and working ability in a technical field, e.g. Electrical Engineering, Embedded Systems, Computer Science, or similar.

•    Demonstrable experience with software development in C#/.NET.

•    Affinity with or experience in IoT/telematics hardware, such as GPS trackers, CAN-bus interfaces, and sensors.

•    Experience with Ruptela, Teltonika, and Digital Matter hardware is a plus.

•    Knowledge of communication protocols such as CAN, LVCAN, OBD-II, MQTT, and/or TCP/IP is a plus.

•    Experience reading, configuring, or updating firmware on embedded devices is a plus.

•    Experience building test or simulation tools (e.g. device or protocol simulators) and with test automation (unit/integration tests) is a plus.

•    Experience with DevOps practices and CI/CD pipelines (incl. Azure DevOps) is a plus.

•    Affinity with AI/machine learning, for example training models for simulations and test setups, is a plus.

•    You're analytical and structured: you enjoy bringing order to a wide range of device configurations and documenting what you find.

•    You value quality assurance and structurally build testability into your own work.

•    You're proficient in English, spoken and written (the team's working language); Dutch is not required.

Build smart energy solutions combining IoT sensors, edge computing, and real-time analytics.

What you'll do:

• Develop solar panel monitoring systems (Raspberry Pi/ESP32)
• Implement MQTT brokers and time-series databases (InfluxDB)
• Create energy optimization algorithms (ML-based forecasting)
• Build dashboards (Grafana, custom React apps)
• Deploy edge AI models for predictive maintenance
• Integrate with smart grid protocols

What we need:

• Python, basic electronics
• Arduino/ESP32 projects
• Interest in renewable energy/IoT
• Cloud basics (MQTT, AWS IoT Core)

Impact:

• Systems deployed at 50+ solar installations
• Green tech portfolio for sustainability roles
• Patent publication opportunity

Greetings from Skoegle IoT Innovations Pvt Ltd 

Job Summary

We are looking for an experienced Embedded Firmware Engineer with expertise in embedded systems, firmware architecture, RTOS, and embedded software development for IoT, wearable, automotive, industrial, and medical-grade products.

Key Responsibilities

• Design, develop, debug, and maintain firmware in C, C++, and Embedded C.

• Develop firmware for ESP32, nRF52832/52840, ATmega328P, and Raspberry Pi platforms.

• Integrate sensors using I2C, SPI, UART, ADC, GPIO, PWM, CAN, and USB.

• Develop RTOS and bare-metal firmware.

• Implement BLE, GSM/4G, GPS/GNSS, LoRa, Wi-Fi, NFC/RFID communication.

• Design bootloaders, OTA updates, and secure firmware upgrades.

• Optimize power consumption, sleep modes, memory allocation, and performance.

• Develop sensor drivers, calibration routines, and medical-grade firmware.

• Program bare ICs and support PCB bring-up, pin selection, and hardware validation.

• Support HTTP/HTTPS GET/POST/PUT APIs and embedded networking.

Required Skills

• Embedded Systems and Embedded Software Development

• C, C++, Embedded C

• RTOS, Bare-Metal Programming

• Operating Systems fundamentals

• I2C, SPI, UART, Digital & Analog Signals

• Sensor Integration

• Arduino IDE, VS Code, SEGGER Embedded Studio, J-Link

• ESP32 Series, nRF52832/52840, ATmega328P, Raspberry Pi

• BLE (UUIDs), GSM (band configuration), GPS, LoRa

• Python, HTML, HTTP/HTTPS

• Bootloader Development, OTA, Power Optimization

• Memory Allocation, Sleep Modes, Sensor Calibration

• Machine Learning on Embedded Systems (preferred)

Job Title: Software/Hardware Engineer (IIT/NIT)

Location: Bangalore

Website: https://www.zeuron.ai

Experience: 1-5Years

CTC: 6-10 LPA

No Freshers

About the Company

Zeuron.ai is a Bangalore-based deep-tech startup founded in 2019, focused on building brain-inspired computing and AI-driven healthcare solutions. The company combines neuroscience, AI, and gaming to create innovative digital therapeutics and neurotechnology platforms for improving brain health, rehabilitation, and overall well-being.

The role

Zeuron.ai is looking for hands-on software engineers who can turn an incomplete brief into reliable, usable software. You will work as an individual contributor, make sound technical decisions and take responsibility for the quality of what you deliver.

AI coding tools will be part of the workflow. We expect you to understand the underlying software well enough to build and debug without an LLM, then use AI to accelerate implementation, exploration and verification. You remain accountable for the result.

What you will own

• End-to-end delivery: clarify requirements, break work into achievable steps, implement features, test them, deploy them and respond to issues after release.

• Product decisions: understand the user problem, question unclear requirements and explain trade-offs between speed, quality, complexity and maintainability.

• Reliable software: investigate defects, identify root causes and improve error handling, performance and usability.

• Engineering continuity: maintain readable code, useful documentation and clear handovers so that others can run, understand and extend your work.

Engineering expectations

We value demonstrated building ability, technical reasoning and sound judgement. Tool familiarity should be supported by evidence of software you have actually delivered.

Software fundamentals

• Programming: practical fluency in at least one programming language, with an understanding of data structures, control flow, modularity and common complexity trade-offs.

• Applications and services: understand how interfaces, APIs, business logic and data storage interact. Be able to trace a failure across these boundaries.

• Data: work with databases, reason about data models and queries, and handle validation, consistency and errors appropriately.

• Development workflow: use Git confidently, review changes, manage dependencies and keep development and deployment instructions reproducible.

• Testing and debugging: reproduce failures, form hypotheses, inspect logs and isolate causes. Test important behaviour and edge cases rather than relying on a successful demo.

• Security and reliability: recognise basic risks around authentication, access control, secrets, input handling and third-party dependencies.

Build independently. Use AI effectively.

• Without LLMs: write and modify code, diagnose defects, explain design choices and use documentation to solve unfamiliar problems independently.

• With AI coding tools: frame tasks clearly, supply relevant context, use generated suggestions selectively and inspect the resulting changes.

• Verify before accepting: check correctness, integration, security and maintainability. Recognise invented APIs, fragile assumptions and plausible-looking code that does not solve the actual problem.

• Protect information: use approved tools and handle credentials, proprietary code and user data responsibly.

Evidence we want to discuss

Be prepared to walk through a project you contributed to: the problem, your specific contribution, important technical decisions, a difficult bug and how you verified the result. Public repositories or demos are useful where available; do not share confidential material from previous employers.

Ownership, growth & applying

How you will work

• Act as an owner: follow through on agreed deliverables, raise blockers early and communicate progress with concrete evidence.

• Work with the team: collaborate with product and engineering colleagues, accept review constructively and explain technical choices clearly.

• Learn with purpose: pick up unfamiliar tools when the problem requires them, while keeping the solution proportionate to the need.

• Grow through contribution: begin with hands-on individual-contributor responsibility, with potential to take on broader product or team responsibility as delivery, judgement and collaboration develop.

What strong performance looks like

Working features that meet agreed requirements; clear reasoning about implementation; defects investigated systematically; code that others can maintain; and AI-assisted work whose quality you can explain and verify.

Eligibility and compensation

Experience: 1-5 years of hands-on software development experience only.

Freshers are not considered.

Locations: Bengaluru and Belagavi.

Annual CTC : 6-10 LPA

The offer will depend on experience, interview performance and growth potential.

What to expect in the assessment

Be prepared for a discussion of your previous work, a practical coding or debugging task without LLM assistance, and an assessment of how you use AI coding tools and verify their output. We will also discuss product judgement, ownership and collaboration.

• Develop python-based automation for large data sets data analysis for vulnerability management reporting.
• Leverage machine learning in the process as required.
• Develop Prompts to automate test data extraction process from databases.
• Provide technical expertise through a hands-on approach to teams and projects.
• Experience with one or more general purpose programming languages including but not limited to: Java, Python, R or equivalent
• Experience and knowledge in designing, building, and deploying multi layered application Infrastructure involving On-premises & AWS Cloud platform using services BedRock LLM models.
• Handle design, definition, planning and development.
• 100% adherence to architectural and development best practices including the use of standard architectures, proper use of code management, document design and design artifacts and conduct design/code reviews.
• Create optimization plans to innovate, shift-left, and mitigate gaps.
• Apply cloud concepts and capabilities to deliver testing for cloud-hosted apps.
• Report succinct testing goals and results to the leadership.
• Train and educate various teams on SV ideas and expectations.
• Expand responsibilities to drive test data, test environment, and service virtualization strategies.

Cybersecurity Engineer – AI Training Project

About the Opportunity

We’re looking for experienced Cybersecurity Engineers to contribute technical expertise to a customer project focused on improving the capabilities of next-generation AI systems.

In this role, you’ll use your real-world experience in cybersecurity, software engineering, vulnerability assessment, and secure development to create high-quality technical inputs that help AI systems better understand, debug, secure, and reason about complex software.

What You’ll Do

• Analyze, debug, and resolve software bugs, vulnerabilities, and security issues across complex codebases.
• Review source code and identify potential security weaknesses, vulnerabilities, and attack vectors.
• Perform security assessments, vulnerability assessments, penetration testing, and codebase audits.
• Develop and modify software using languages such as Python, Java, Rust, Go, C++, or TypeScript.
• Implement new features and fix existing functionality while maintaining strong security and engineering standards.
• Refactor legacy code to improve security, maintainability, reliability, and performance.
• Work on backend systems and help optimize applications for scalability, performance, and security.
• Analyze real-world security scenarios and translate your expertise into high-quality technical examples and problem-solving tasks.
• Document technical findings, vulnerabilities, debugging approaches, and recommended solutions.
• Provide domain expertise that helps improve how AI systems reason about software engineering and cybersecurity problems.

What We’re Looking For

• Strong professional experience in Cybersecurity / Application Security / Product Security / DevSecOps / Penetration Testing / Vulnerability Management.
• Strong programming experience in one or more of:
• Python
• Java
• Rust
• Go
• C++
• TypeScript
• Proven experience with debugging, troubleshooting, and fixing complex software issues.
• Hands-on experience with penetration testing, vulnerability assessment, security auditing, or application security.
• Understanding of secure software development practices and modern security threats.
• Strong knowledge of data structures, algorithms, software architecture, and code quality.
• Ability to review unfamiliar codebases and quickly understand how systems work.
• Strong written communication and the ability to explain complex technical findings clearly.

Nice to Have

• Experience with OWASP, API security, cloud security, DevSecOps, or threat modeling.
• Experience performing security assessments on production applications or enterprise systems.
• Experience with tools such as Burp Suite, Metasploit, Nmap, Wireshark, SAST/DAST tools, or vulnerability scanners.
• Contributions to open-source security or software projects.
• Experience working with AI/ML systems, LLMs, data annotation, or AI training projects.
• Relevant security certifications such as OSCP, OSWE, CEH, CISSP, Security+, or equivalent practical experience.

Engagement

• Role: Cybersecurity Engineer
• Work: Remote(Contract)
• Experience: Mid-level to Senior
• Programming: Required
• Cybersecurity expertise: Required

Why Join?

This is an opportunity to apply your existing cybersecurity expertise to an emerging area of technology. Your practical experience debugging software, identifying vulnerabilities, securing applications, and solving complex engineering problems will directly contribute to improving the capabilities of next-generation AI systems.

If you enjoy breaking down complex technical problems, finding vulnerabilities, fixing software, and thinking deeply about how systems work, this project could be a strong fit.

Role Overview

As a Software Engineer, you will build and maintain features across our SaaS platform. You will work on well-scoped tasks and features, collaborate closely with senior engineers, and grow your skills in software design, cloud-native development, and modern engineering practices. This role is a great fit for engineers who have solid programming fundamentals, are curious and quick to learn, and take pride in writing quality code. You will be supported and mentored while taking on increasing ownership over time.

Required Qualifications

Bachelor’s or Master’s degree in Computer Science or a related discipline.·       

5–8 years of software engineering experience building production-grade applications.

Strong experience building and operating cloud-native SaaS or web applications.

Solid understanding of software design, distributed systems, and modern engineering practices.

Proven ability to own and deliver complex features independently.

Experience debugging and resolving performance, scalability, and reliability issues.

What We Look For

Strong programming fundamentals and a quality mindset.

Curiosity and a strong desire to learn and grow.

Ability to deliver well-scoped tasks reliably.

Good problem-solving and debugging skills.

Collaboration and communication skills.

Ownership and accountability for the work you do.

Passion for building software and continuous learning.

Role Overview 

We are looking for an AI Engineer to design, build, and ship production AI systems, including agentic AI applications, for enterprise clients. This is a hands-on engineering role: you will write production code, build and evaluate models and agents, and work closely with architects and product teams to take solutions from prototype to scale. 

Key Responsibilities 

Design and build agentic AI systems: agent workflows, tool/function-calling, memory, and human-in-the-loop patterns. Build and productionise RAG pipelines, prompt-based applications, and LLM integrations across providers. Develop and maintain data and ML pipelines: feature engineering, model training, evaluation, and monitoring. Integrate AI systems with enterprise applications (CRMs, ERPs, ITSM tools) via APIs, events, and MCP-based tool servers. Implement guardrails, prompt-injection defences, and evaluation frameworks to keep AI systems safe and reliable in production. 

Write clean, tested, production-grade code and participate actively in code and design reviews. 

Collaborate with architects, product managers, and delivery teams to translate requirements into working AI solutions. Troubleshoot and optimise AI systems for accuracy, latency, and cost in production. 

Required Qualifications 

8–12 years of hands-on software engineering experience, with a strong, unbroken technical track record. Hands-on experience building and shipping AI/ML systems in production, not just POCs. 

Practical experience with agentic AI systems and at least one major agent framework (LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, Bedrock Agents/Strands, or Semantic Kernel). 

Experience with LLM/GenAI systems: RAG pipelines, prompt engineering, structured outputs, and tool calling across providers. 

Strong Python skills (TypeScript/Node.js a plus), with production-grade testing, CI/CD, and API design practices. Working knowledge of ML fundamentals: model evaluation, feature engineering, and experimentation. Cloud-native experience on AWS and/or Azure: containers, serverless, event backbones, and vector databases. Understanding of LLM safety and reliability practices: guardrails, prompt-injection defences, and observability.