Assistant Software Engineer

About Us

We believe the future of software development is AI-native — where engineers operate at a higher level of abstraction and quality remains non-negotiable. 

Incubyte is a software craft consultancy where the “how” of building software matters as much as the “what”.  

We partner with companies of all sizes, from helping enterprises build, scale, and modernize to early-stage founders bring their ideas to life. 

Our engineers operate in an AI-native development model, using AI as a collaborator across the SDLC to accelerate development while upholding the discipline of software craftsmanship. Guided by Software Craftsmanship and Extreme Programming practices, we build reliable, maintainable, and scalable systems with speed, without compromising quality. If this way of building software resonates with you, we’d like to talk. 

Our Guiding Principles 

These principles define how we work at Incubyte. They are non-negotiable. 

Relentless Pursuit of Quality with Pragmatism 

  We build high-quality systems without losing sight of delivery. 

Extreme Ownership 

  We take responsibility end-to-end for decisions, execution, and outcomes. 

Proactive Collaboration 

  We collaborate closely, challenge each other, and solve problems together. 

Active Pursuit of Mastery 

  We continuously improve our craft and raise our bar. 

Invite, Give, and Act on Feedback 

We seek, give, and act on feedback to get better every day. 

Ensuring Client Success 

We act as trusted partners and focus on real outcomes, not just output. 

Experience Level

This role is ideal for engineers with total 3+ years of experience with a proven track record of shipping complex projects successfully.

An experienced individual contributor and leader who thrives in large, complex projects with widespread impact.

What You’ll Do as a Software Craftsperson 

• Design and build high-quality, maintainable systems using disciplined engineering practices such as TDD, continuous refactoring, and pair programming 
• Operate in an AI-native development model, using AI as a collaborator to explore architecture and design, accelerate development, and continuously improve systems while applying strong judgment to ensure that speed never compromises quality 
• Take end-to-end ownership of outcomes from problem understanding and system design to implementation, deployment, and operation in production 
• Make thoughtful design decisions that balance simplicity, scalability, and long-term maintainability in real-world systems 
• Maintain a high bar for engineering quality through rigorous testing, code reviews, and continuous feedback 
• Investigate and resolve production issues, and implement systemic improvements to prevent recurrence 
• Work directly with clients, navigate ambiguity, and translate business problems into well-designed technical solutions 
• Contribute to improving team practices, tooling, and systems to raise the overall quality and effectiveness of engineering 

Requirements

What You’ll Bring 

• 3+ years of experience building high-quality, production systems (flexible based on demonstrated capability) 
• Strong fundamentals in software engineering, including object-oriented design, system design, and testing practices such as TDD 
• Demonstrated ability to build simple, maintainable, and scalable systems with a focus on long-term reliability 
• Proficiency in one or more modern technologies, Python, PHP, JavaScript, or TypeScript, with the ability to learn new technologies quickly 
• Deep experience working with Git in collaborative environments, including managing shared codebases, conducting code reviews, and maintaining a high bar for quality 
• Ability to operate effectively in an AI-native workflow using AI as a collaborator to explore solutions and accelerate development, while applying strong judgment to ensure correctness, quality, and maintainability 
• Clear thinking and strong problem-solving ability, with the capacity to break down complex problems into simple, well-structured solutions 
• A strong sense of ownership — you take responsibility for outcomes, care deeply about quality, and are not comfortable shipping work that does not meet your standards.

Benefits

Life at Incubyte 

We are a remote-first company with structured flexibility. Teams commit to shared rhythms during core hours, ensuring smooth collaboration while maintaining autonomy. Twice a year, we come together in person for a co-working sprint and once a year for a retreat - with all travel expenses covered. 

Our environment is built for crafters: pairing, refactoring, experimenting with AI, and pushing the boundaries of software excellence. We are all lifelong learners, and our work is our passion. 

Perks

• Dedicated learning & development budget. 
• Sponsorship for conference talks. 
• Comprehensive medical & term insurance. 
• Employee-friendly leave policies. 
• Home Office fund 
• Medical Insurance

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.

About the role

We are seeking an AI Engineer to build and implement AI systems for content production at scale. You'll work at the intersection of engineering and content designing prompt pipelines, integrating generative models, and building the tooling that turns source material into finished creative output. The ideal candidate is technically strong but also has taste: someone who understands story and craft, and can tell the difference between output that's technically correct and output that's actually good.

Responsibilities

• Build and iterate on prompt pipelines and multi-agent workflow components
• Design and integrate agentic workflows orchestrate multi-step, tool-using agents that plan, call models, and hand off between stages in production
• Deploy and serve open-source models set up inference endpoints, manage GPU compute, and optimize for latency and cost
• Write evals compare outputs against references, quantify quality, and feed results back into the pipeline
• Work on data pipelines: structured extraction from messy source text, localization, similarity/dedup
• Debug and maintain pipeline stages in production

What you bring:  

• (1+/3+) years of engineering experience, or a strong portfolio of shipped projects
• Solid Python fundamentals clean, working, readable code
• Hands-on experience with LLM APIs and prompt engineering (personal projects count)
• Comfort with Git, REST APIs, and working in a Linux environment
• A feel for content and narrative you can judge whether generated output is actually good, not just valid
• Curiosity and clear communication you ask good questions and don't stay stuck silently

 Preferred

• Exposure to agent/orchestration frameworks (LangGraph, LangChain, CrewAI)
• Familiarity with vector databases, embeddings, or RAG (Qdrant, pgvector)
• Hands-on work with open-source generative media models Flux, LTX, Wan, or similar
• Experience deploying open-source models for inference (vLLM, ComfyUI, Replicate/Cog, Docker + GPU)
• Experience writing evals or LLM-as-judge scoring
• Node.js and Fastapi familiarity, or experience deploying on AWS

About the role

We are seeking an AI Engineer to build and implement AI systems for content production at scale. You'll work at the intersection of engineering and content designing prompt pipelines, integrating generative models, and building the tooling that turns source material into finished creative output. The ideal candidate is technically strong but also has taste: someone who understands story and craft, and can tell the difference between output that's technically correct and output that's actually good.

Responsibilities

• Build and iterate on prompt pipelines and multi-agent workflow components
• Design and integrate agentic workflows orchestrate multi-step, tool-using agents that plan, call models, and hand off between stages in production
• Deploy and serve open-source models set up inference endpoints, manage GPU compute, and optimize for latency and cost
• Write evals compare outputs against references, quantify quality, and feed results back into the pipeline
• Work on data pipelines: structured extraction from messy source text, localization, similarity/dedup
• Debug and maintain pipeline stages in production

What you bring:  

• (1+/3+) years of engineering experience, or a strong portfolio of shipped projects
• Solid Python fundamentals clean, working, readable code
• Hands-on experience with LLM APIs and prompt engineering (personal projects count)
• Comfort with Git, REST APIs, and working in a Linux environment
• A feel for content and narrative you can judge whether generated output is actually good, not just valid
• Curiosity and clear communication you ask good questions and don't stay stuck silently

 Preferred

• Exposure to agent/orchestration frameworks (LangGraph, LangChain, CrewAI)
• Familiarity with vector databases, embeddings, or RAG (Qdrant, pgvector)
• Hands-on work with open-source generative media models Flux, LTX, Wan, or similar
• Experience deploying open-source models for inference (vLLM, ComfyUI, Replicate/Cog, Docker + GPU)
• Experience writing evals or LLM-as-judge scoring
• Node.js and Fastapi familiarity, or experience deploying on AWS

About the role

We give you a product design and a brief. You turn it into backend software that analyses images and user input and hands our frontend team the structured data it needs.

Most of the code gets written by AI agents like Claude Code and Codex, with you directing them. That makes you responsible for every line they produce, including the wrong ones. Your value is knowing what to ask for and catching what the agent got wrong. If “the AI did it” sounds like a reasonable defence to you, this job will frustrate you.

What you will do

1. Read a design and work out what data each part of it needs.
2. Build the backend logic that produces that data, with AI coding agents doing most of the typing.
3. Set up open-source computer vision and AI models, run them on real images, and decide whether they are good enough.
4. Check your own output before anyone reviews it. Wrong values, invented APIs and messy code should stop with you.
5. Ship small, well-typed pull requests that get through code review.

You won’t have to come up with the product itself. We do that part, and your job is to make it work and keep it maintainable.

You will fit if you

1. Write clear, precise English in prompts, pull requests and messages. This is the first thing we screen for.
2. Use Claude Code, Codex or Cursor every day, and can show us how you break a task down for an agent.
3. Know enough computer vision, machine learning and data engineering to ask for the right thing and to recognise a wrong answer when you see one.
4. Are a solid Python engineer who understands typing and async, and who spots bad patterns in a diff quickly.
5. Look at the actual output every time. Code that runs proves very little.

Nice to have

1. Experience with OpenCV or similar image libraries.
2. Experience with FastAPI, workflow engines, or cloud storage.
3. Experience getting structured outputs from LLM APIs.
4. A side project where you got an open-source model running and evaluated it.

How to apply

Send your CV and answers to these 3 questions, 150 words maximum each:

1. Describe one time an AI coding agent gave you code that looked right but was wrong. How did you find out?
2. You must estimate the real-world size of an object from a single photo. What steps and checks would you ask an AI agent to build?
3. Paste one real prompt you recently gave an AI coding agent, and tell us what happened next.

Include a link to one piece of your work: a repository, pull request, write-up or demo.

AI / Backend Engineer — Remote (India / Overseas)

Company: Ink'd

Compensation: $1,500–$2,500 USD/month, depending on experience

Type: Independent contractor, long-term opportunity

Ink'd is building a voice-first AI platform for residential real estate transactions. Our AI assistant allows real estate agents to generate contracts, automate workflows, and complete transaction documentation through natural conversation.

We're looking for a highly capable AI/backend engineer to help scale and maintain our production platform.

Responsibilities

• Build and maintain production AI agent workflows
• Develop integrations with third-party APIs and services
• Work with LLMs, structured data extraction, and document generation
• Troubleshoot production systems and improve reliability
• Build scalable backend services and maintain databases
• Collaborate directly with the founder and engineering team

Technical experience

• Python, FastAPI, Node.js, and REST APIs
• LLM APIs, tool calling, and agent orchestration
• PostgreSQL and cloud infrastructure
• GitHub, CI/CD, debugging, and deployment
• Experience with voice AI, WebSockets, or document processing is a major plus

What we're looking for

Someone who has independently shipped production software, can troubleshoot unfamiliar systems, communicates clearly, and takes ownership of their work.

Please include your GitHub, two examples of production systems you've built, your specific contributions, monthly compensation expectations, and availability.

Solid product experience and an educational background from Tier‑1 universities are preferred.

As a Senior AI Engineer, you will play a key role in designing and delivering highly scalable, next generation AI products within our AI stack. You will work in a technically rich environment with talented peers, contributing to product planning, design, and execution while influencing the evolution of Teradata’s AI capabilities. 

In this role, you will: 

• Design, develop, and maintain high quality systems, services, and applications with an emphasis on scalability, reliability, and performance. 
• Collaborate with cross-functional engineers and product partners to shape design and consistently deliver end to end features. 
• Build and integrate robust RESTful APIs, ensuring security, data consistency, and maintainability. 
• Work with SQL and NoSQL databases to implement efficient data models and service access patterns. 
• Apply and experiment with AI/ML technologies, including agentic AI and large language models (LLMs). 
• Use AI powered engineering tools to improve development quality, speed, and productivity. 
• Mentor engineers, supporting them in technical planning, implementation, and best practices. 
• Identify and resolve system performance bottlenecks, optimizing code, design, and infrastructure. 
• Write unit and integration tests and participate in code reviews to uphold engineering excellence. 
• Investigate production issues, ensuring timely and effective solutions. 
• Stay current with emerging trends in engineering, AI/ML, and cloud-native technologies. 

Who You’ll Work With 

You will be part of a high-performing engineering team building core components of Teradata’s AI platform. You will collaborate closely with other engineers, AI/ML specialists, product managers, cloud architects, and partner teams across the company. The role offers opportunities to contribute directly to Teradata’s AI product roadmap and technological direction. 

What Makes You a Qualified Candidate 

(Nonnegotiable qualifications) 

• Bachelor’s degree in Computer Science or equivalent from a recognized institution. 
• 5+ years of experience in backend services, distributed systems, or data platform development. 
• Strong proficiency in Java, Go, or Python for service development. 
• Good understanding of design principles, distributed system patterns, and service framework. 
• Hands-on experience designing and developing RESTful APIs. 
• Experience with SQL and NoSQL databases and data modelling. 
• Strong debugging, problem solving, and troubleshooting skills. 
• Experience with modern containerization and orchestration tools such as Kubernetes. 
• Knowledge of public cloud platforms. 
• Experience with AI productivity tools (e.g., GitHub Copilot). 
• Ability to work independently, drive workstreams, and deliver high quality outcomes. 
• Strong communication and collaboration skills. 

What You’ll Bring 

(Preferred qualifications) 

• Familiarity with messaging systems such as Kafka. 
• Experience experimenting with or implementing AI/ML technologies, Agentic AI, or LLMs. 
• A track record of influencing design decisions and driving engineering best practices. 
• The ability to mentor engineers and guide them through design, planning, and execution. 
• A proactive mindset and comfort working in fast paced, dynamic environments. 
• Curiosity, adaptability, and a passion for building impactful AI-driven products. 

About NonStop io Technologies

NonStop io Technologies is a value-driven company with a strong focus on process-oriented software engineering. We specialize in Product Development and have a decade's worth of experience in building web and mobile applications across various domains. NonStop io Technologies follows core principles that guide its operations and believes in staying invested in a product's vision for the long term. We are a small but proud group of individuals who believe in the 'givers gain' philosophy and strive to provide value in order to seek value. We are committed to and specialize in building cutting-edge technology products and serving as trusted technology partners for startups and enterprises. We pride ourselves on fostering innovation, learning, and community engagement. Join us to work on impactful projects in a collaborative and vibrant environment.

Brief Description:

We're seeking an AI/ML Engineer to join our team. As AI/ML Engineer, you will be responsible for designing, developing, and implementing artificial intelligence (AI) and machine learning (ML) solutions to solve real-world business problems. You will work closely with engineering teams, including software engineers, domain experts, and product managers, to deploy and integrate Applied AI/ML solutions into the products that are being built at NonStop io. Your role will involve researching cutting-edge algorithms and data processing techniques, and implementing scalable solutions to drive innovation and improve the overall user experience.

Responsibilities

● Applied AI/ML engineering; Building engineering solutions on top of the AI/ML tooling available in the industry today. Eg: Engineering APIs around OpenAI

● AI/ML Model Development: Design, develop, and implement machine learning models and algorithms that address specific business challenges, such as natural language processing, computer vision, recommendation systems, anomaly detection, etc.

● Data Preprocessing and Feature Engineering: Cleanse, preprocess, and transform raw data into suitable formats for training and testing AI/ML models. Perform feature engineering to extract relevant features from the data

● Model Training and Evaluation: Train and validate AI/ML models using diverse datasets to achieve optimal performance. Employ appropriate evaluation metrics to assess model accuracy, precision, recall, and other relevant metrics

● Data Visualization: Create clear and insightful data visualizations to aid in understanding data patterns, model behaviour, and performance metrics

● Deployment and Integration: Collaborate with software engineers and DevOps teams to deploy AI/ML models into production environments and integrate them into various applications and systems

● Data Security and Privacy: Ensure compliance with data privacy regulations and implement security measures to protect sensitive information used in AI/ML processes

● Continuous Learning: Stay updated with the latest advancements in AI/ML research, tools, and technologies, and apply them to improve existing models and develop novel solutions

● Documentation: Maintain detailed documentation of the AI/ML development process, including code, models, algorithms, and methodologies for easy understanding and future reference.

Qualifications & Skills

● Bachelor's, Master's, or PhD in Computer Science, Data Science, Machine Learning, or a related field. Advanced degrees or certifications in AI/ML are a plus

● Proven experience as an AI/ML Engineer, Data Scientist, or related role, ideally with a strong portfolio of AI/ML projects

● Proficiency in programming languages commonly used for AI/ML. Preferably Python

● Familiarity with popular AI/ML libraries and frameworks, such as TensorFlow, PyTorch, scikit-learn, etc.

● Familiarity with popular AI/ML Models such as GPT3, GPT4, Llama2, BERT etc.

● Strong understanding of machine learning algorithms, statistics, and data structures

● Experience with data preprocessing, data wrangling, and feature engineering

● Knowledge of deep learning architectures, neural networks, and transfer learning

● Familiarity with cloud platforms and services (e.g., AWS, Azure, Google Cloud) for scalable AI/ML deployment

● Solid understanding of software engineering principles and best practices for writing maintainable and scalable code

● Excellent analytical and problem-solving skills, with the ability to think critically and propose innovative solutions

● Effective communication skills to collaborate with cross-functional teams and present complex technical concepts to non-technical stakeholders

Job Overview

We are looking for an experienced AI/ML Engineer with strong full-stack development skills to design, develop, and deploy AI-powered applications. The ideal candidate should be proficient in Python backend development, frontend technologies, and LLM integration, with the ability to build end-to-end AI-native products, custom dashboards, and lightweight applications.

This role focuses on applying AI to real-world business problems through rapid prototyping, prompt engineering, Retrieval-Augmented Generation (RAG), and scalable application development.

Key Responsibilities

• Design, develop, and deploy end-to-end AI-powered applications.
• Build backend services and REST APIs using Python.
• Develop responsive frontends using React, Next.js, or similar frameworks.
• Integrate LLM APIs such as OpenAI, Claude, and Hugging Face into production applications.
• Build custom dashboards, internal tools, micro-apps, and AI-driven business solutions.
• Implement prompt engineering, embeddings, RAG pipelines, and context-aware AI systems.
• Rapidly prototype and validate ideas using modern AI-assisted development workflows.
• Optimize application performance, scalability, reliability, and AI usage costs.
• Work with data processing libraries such as Pandas and NumPy.
• Collaborate with product and business teams to translate requirements into functional AI solutions.
• Take ownership of features from ideation and development through testing, deployment, and production support.

Required Skills & Qualifications

• 2+ years of experience in software engineering, AI engineering, or application development.
• Strong proficiency in Python and backend development.
• Hands-on experience with React, Next.js, or similar frontend technologies.
• Practical experience integrating LLM APIs such as OpenAI, Claude, or Hugging Face.
• Understanding of REST APIs, microservices, and system design principles.
• Knowledge of prompt engineering, embeddings, and RAG architectures.
• Experience with data processing using Pandas and NumPy.
• Ability to independently build, test, and deploy full-stack applications.
• Strong problem-solving, debugging, and analytical skills.
• Ability to work in a fast-paced environment with a strong ownership mindset.

Good to Have

• Experience with LangChain, LlamaIndex, or similar AI frameworks.
• Familiarity with vector databases such as Pinecone, Weaviate, or Supabase.
• Experience building AI chat interfaces, copilots, assistants, and custom dashboards.
• Familiarity with cloud platforms, application deployment, and production monitoring.
• Experience with AI-assisted coding tools and rapid prototyping workflows.

What We Are Looking For

• A full-stack AI engineer who is comfortable working across both backend and frontend development.
• Someone focused on building practical AI-powered products rather than only training machine learning models.
• A developer who can prototype quickly, validate ideas, and iterate efficiently using a “vibe coding” approach.
• A self-driven professional who can take ownership of a feature from concept to production.

Please note that this job is only for Ahmedabad location.

About Us

We believe the future of software development is AI-native — where engineers operate at a higher level of abstraction and quality remains non-negotiable. 

Incubyte is a software craft consultancy where the “how” of building software matters as much as the “what”.  

We partner with companies of all sizes, from helping enterprises build, scale, and modernize to early-stage founders bring their ideas to life. 

Our engineers operate in an AI-native development model, using AI as a collaborator across the SDLC to accelerate development while upholding the discipline of software craftsmanship. Guided by Software Craftsmanship and Extreme Programming practices, we build reliable, maintainable, and scalable systems with speed, without compromising quality. If this way of building software resonates with you, we’d like to talk. 

Our Guiding Principles 

These principles define how we work at Incubyte. They are non-negotiable. 

Relentless Pursuit of Quality with Pragmatism 

 We build high-quality systems without losing sight of delivery. 

Extreme Ownership 

 We take responsibility end-to-end for decisions, execution, and outcomes. 

Proactive Collaboration 

 We collaborate closely, challenge each other, and solve problems together. 

Active Pursuit of Mastery 

 We continuously improve our craft and raise our bar. 

Invite, Give, and Act on Feedback 

We seek, give, and act on feedback to get better every day. 

Ensuring Client Success 

We act as trusted partners and focus on real outcomes, not just output. 

Job Description

This is a remote position.

This is a remote position.

Experience Level

This role is ideal for engineers with 3–6 years of experience and a strong background in building scalable, production-grade software systems.

We are looking for hands-on Software Engineers with deep expertise in Python and TypeScript, with exposure to AI/LLM systems and modern infrastructure tooling.

What You’ll Do as a Software Craftsperson

•     Take full ownership of the software development lifecycle for complex, cross-functional initiatives — from design through production readiness.

•     Build and maintain robust, scalable backend systems and APIs using Python and TypeScript, following clean code and software craftsmanship principles.

•     Design and deliver features end-to-end, balancing scope, quality, and long-term maintainability.

•     Identify technical and product issues beyond the immediate scope of work, proactively raising risks and driving solutions.

•     Shape team practices around code quality, testing, tooling, and continuous improvement using DevEx and DORA principles.

•     Collaborate closely with clients and internal teams to understand requirements, clarify priorities, and align on outcomes.

•     Mentor and guide fellow engineers to raise overall team performance and promote a culture of learning.

•     Leverage AI tools (LLMs, agentic frameworks, etc.) to accelerate design, development, testing, and delivery where applicable.

Requirements

What You’ll Bring

3–6 years of overall software engineering experience with a strong track record of owning and delivering complex production systems.

Must-Have Skills

•     Python (must-have): Deep expertise in writing idiomatic, testable, production-grade Python — including advanced OOP, data structures, algorithms, and software engineering best practices.

•     TypeScript (must-have): Strong proficiency in building and maintaining type-safe, scalable applications across frontend and/or backend TypeScript codebases.

•     Strong system design skills: ability to architect scalable, maintainable, and observable systems with a focus on reliability and long-term operability.

•     Solid engineering practices: experience with TDD, CI/CD, code reviews, refactoring, and continuous deployment in Agile or eXtreme Programming environments.

•     Working knowledge of relational databases, web server ecosystems, REST/gRPC APIs, and performance optimisation.

•     Experience with source control, bug tracking, user story writing, and maintaining clear technical documentation.

Good-to-Have Skills

•     AI / LLM experience: hands-on exposure to building applications using LLMs (GPT, Claude, Gemini, or similar) for tasks such as document classification, entity extraction, or structured data generation.

•     LLM orchestration frameworks: familiarity with LangChain, LlamaIndex, Mastra, Agno, or similar agentic frameworks.

•     Prompt engineering: experience refining prompts and orchestration patterns to improve response accuracy, consistency, and structured outputs.

•     Vector databases and observability tooling: exposure to tools like Pinecone, PgVector, Qdrant, LangSmith, or DeepEval.

•     Container orchestration and infrastructure-as-code: experience with Kubernetes, Terraform, and Docker for deploying and managing production workloads.

Benefits

Life at Incubyte

We are a remote-first company with structured flexibility. Teams commit to shared rhythms during core hours, ensuring smooth collaboration while maintaining autonomy. Twice a year, we come together in person for a co-working sprint and once a year for a retreat — with all travel expenses covered.

Our environment is built for crafters: experimenting with real-world systems, solving complex infrastructure challenges, and contributing to cutting-edge AI initiatives. We are all lifelong learners, and our work is our passion.

Perks

•     Dedicated learning & development budget

•     Sponsorship for conference talks

•     Comprehensive medical & term insurance

•     Employee-friendly leave policies

•     Home Office fund

•     Medical Insurance