Why Kimchi?

Kimchi is the AI platform inside CAST AI. We started by helping companies run LLMs on their own Kubernetes clusters - now we're building the execution layer where agents do real work.

Our Infrastructure today: multi-model inference (MiniMax, Kimi, GLM-5, Nemotron, DeepSeek) with intelligent routing, an OpenAI-compatible API, and deployment flexibility from our GPUs to your VPC. The inference layer is the foundation. What we're hiring for sits on top of it: coding agents, agent runtimes, orchestration systems, and the reliability engineering that makes them actually finish things.

Tech Stack: TypeScript, Go, Kubernetes, AWS/GCP/Azure, MCP, Prometheus/Grafana/Loki, GitLab CI, ArgoCD.

Why harness engineering matters here
OpenAI and Anthropic ship models. They also ship one harness each - the scaffolding that turns a raw model into something that can plan, execute, recover, and complete work. We ship a different kind of harness: one built for cost-conscious, long-horizon autonomy, running on inference infrastructure we control end-to-end.
A decent model with a great harness beats a great model with a bad harness. We've watched this play out. The gap between what today's models can do and what you see them doing is largely a harness gap - and that gap is where we operate.

What you'll build
The ratchet.
Every time our agent makes a mistake, we engineer a solution so it never makes that mistake again. That means hooks that enforce constraints the model "knows" but forgets: pre-commit lint checks, permission gates, context compaction before the window fills. Success is silent, failures are verbose.

Long-horizon execution.
Our harness is built around spec-driven autonomy: meta-prompting, fresh context per task, worktree-per-slice git strategy, automatic replanning, crash recovery, stuck detection. We're implementing Ralph loops - when the model tries to exit, we intercept and reinject the goal into a fresh context. The agent reads state from disk and continues. Multi-session, multi-day work, without context rot.

Planner/executor splits.
Planning with a reasoning model, executing with a fast one, evaluating with a third. Separating generation from evaluation beats self-verification because agents reliably skew positive when grading their own work.

The harness surface.
CLI, TUI, MCP integration, sandboxed execution, telemetry. Our AGENTS.md is short - every line traces to a specific thing that went wrong. TypeScript on the surface, Go where it matters.

Memory and context.
Moving agents off laptops, giving them state that survives across sessions, managing context so information lands where it's actionable. Compaction, tool-call offloading, progressive skill disclosure.

What makes this different (with receipts)
You've seen the pitch: "we route to the best model." Everyone says that. Here's what we actually have:

• GPU infrastructure we own. Not just an API reseller. From GPU placement across clouds to the inference endpoint your agent calls - we control the cost curve.
• A harness-first thesis. We treat agent failures as configuration problems, not model problems. When we moved from a stock harness to our own, completion rates on internal benchmarks improved by 40%+ on the same model.
• Agents.md that earns every line. No brainstormed rules - every constraint in our system prompt traces to a real failure we saw and fixed.

Requirements:

• You've used AI coding agents in anger. Not demos - real work. You have opinions about Claude Code, Codex, OpenCode, Cursor. You know what it feels like when an agent gets stuck and why.
• Strong TypeScript or Go in production. Comfort moving between them. Our surface is TypeScript; our core is Go.
• You think in harness terms. You read "the agent hallucinated" and your first instinct is to ask what context it was missing, what hook should have caught it, what constraint should exist.
• You drive features end-to-end. Design → build → ship → measure → iterate. We don't have layers that absorb ambiguity for you.

Responsibilities:

• Build and evolve the agent harness - ship hooks, permission gates, and context compaction. Every AGENTS.md constraint traces to a failure you personally diagnosed.
• Own long-horizon execution - multi-session task completion via spec-driven prompting, worktree-per-slice git, Ralph loop recovery, and stuck detection. Completion rate is your metric.
• Architect planner/executor/evaluator pipelines - planning with a reasoning model, execution with a fast one, evaluation with a third. No self-verification.
• Manage agent memory and context - state persistence across sessions, context compaction, tool-call offloading. Zero context rot on multi-day work.
• Own the harness surface - CLI, TUI, MCP integrations, sandboxed execution, telemetry. TypeScript on the surface, Go where it matters.

What success looks like (after 6 months):

• You've shipped at least one major harness feature end-to-end: designed it, built it, measured it, iterated.
• You've added constraints to our AGENTS.md based on failures you personally observed and diagnosed.
• You've improved a measurable reliability metric - completion rate, context efficiency, or cost per successful task.
• You've formed strong opinions about where our harness is load-bearing and where it's dead weight.

What’s in it for you?

• Competitive salary (€6,500 - €9,000 gross, depending on the level of experience).
• Enjoy a flexible, remote-first global environment.
• Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology
• Equity options.
• Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks.
• Spend 10% of your work time on personal projects or self-improvement. 
• Learning budget for professional and personal development - including access to international conferences and courses that elevate your skills.
• Annual hackathon to spark new ideas and strengthen team bonds.
• Team-building budget and company events to connect with your colleagues.
• Equipment budget to ensure you have everything you need.
• Extra days off to help maintain a healthy work-life balance.

This is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Slovenia, and Ukraine.

*As part of our standard hiring process, we would like to inform you that a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr.
*Please note that Cast AI does not provide any form of visa sponsorship/work permit.

#LI-Remote

We are looking for a Senior/Lead ML Engineer to join us at Exadel. This role works closely with data scientists, software engineers, and subject matter experts in different business areas to build production systems capable of processing multi-document PDFs, with automated document type detection and field extraction at scale.

Why Join Exadel

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks.

From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

About the Client  

The leading provider of vehicle lifecycle solutions, with headquarters in Chicago, enables the companies that build, insure, and replace vehicles to power the next generation of transportation. Its platform delivers advanced mobile, artificial intelligence, and car technologies. It connects a network of 350+ insurance companies, 24,000+ repair facilities, hundreds of parts suppliers, and dozens of third-party data and service providers. The customer's collective solutions enhance productivity and help clients deliver better experiences for end consumers.

What You’ll Do

• Design and implement end-to-end document intelligence pipelines on AWS
• Develop and optimize ML models for document classification, segmentation, and field extraction
• Build scalable data processing systems handling PDFs up to 2000 pages
• Collaborate with subject matter experts to create and refine requirements for extraction
• Own features from research through production deployment and monitoring
• Establish evaluation frameworks and quality metrics for extraction accuracy

What You Bring

• Advanced knowledge of Python (native, Pandas, ScikitLearn, Tensorflow or Pytorch, PyStats, Pydantic)
• Experience with AWS tools for ML Engineering and ML deployment (Sagemaker, Lambda, Cloudformation/CDK, Step Functions)
• Advanced knowledge of SQL and Data Modeling
• Experience with GenAI for document intelligence, including prompt engineering, RAG (Retrieval Augmented Generation), multi-modal models (vision + text), and production deployment using AWS Bedrock or Azure OpenAI APIs
• Experience in experiment design (power analysis and hypothesis testing)
• Proficiency in both written and verbal communication, required for a remote and largely asynchronous work environment
• Demonstrated capacity to clearly and concisely communicate complex technical problems and propose iterative solutions
• Experience owning a feature from concept to production, including proposal, discussion, and execution

Nice to have 

• Experience with document processing tools (AWS Textract, Azure Document Intelligence, or similar OCR/layout detection systems)
• Experience with PDF and Image processing libraries (e.g. PyMuPDF, opnecv, pillow)
• Experience in Machine Learning/ Data Science (e.g., ML algorithm selection, feature engineering, model training, hyperparameter tuning, supervised and unsupervised learning implementation, building a model pipelines, using Machine Learning tools/libraries/frameworks)
• Experience working with AWS big data technologies (Redshift, S3, EMR, Glue, etc.)

English level 

Upper-intermediate 

Legal & Hiring Information 

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel  

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

We are looking for a Senior/Lead ML Engineer to join us at Exadel. This role works closely with data scientists, software engineers, and subject matter experts in different business areas to build production systems capable of processing multi-document PDFs, with automated document type detection and field extraction at scale.

Why Join Exadel

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks.

From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

About the Client  

The leading provider of vehicle lifecycle solutions, with headquarters in Chicago, enables the companies that build, insure, and replace vehicles to power the next generation of transportation. Its platform delivers advanced mobile, artificial intelligence, and car technologies. It connects a network of 350+ insurance companies, 24,000+ repair facilities, hundreds of parts suppliers, and dozens of third-party data and service providers. The customer's collective solutions enhance productivity and help clients deliver better experiences for end consumers.

What You’ll Do

• Design and implement end-to-end document intelligence pipelines on AWS
• Develop and optimize ML models for document classification, segmentation, and field extraction
• Build scalable data processing systems handling PDFs up to 2000 pages
• Collaborate with subject matter experts to create and refine requirements for extraction
• Own features from research through production deployment and monitoring
• Establish evaluation frameworks and quality metrics for extraction accuracy

What You Bring

• Advanced knowledge of Python (native, Pandas, ScikitLearn, Tensorflow or Pytorch, PyStats, Pydantic)
• Experience with AWS tools for ML Engineering and ML deployment (Sagemaker, Lambda, Cloudformation/CDK, Step Functions)
• Advanced knowledge of SQL and Data Modeling
• Experience with GenAI for document intelligence, including prompt engineering, RAG (Retrieval Augmented Generation), multi-modal models (vision + text), and production deployment using AWS Bedrock or Azure OpenAI APIs
• Experience in experiment design (power analysis and hypothesis testing)
• Proficiency in both written and verbal communication, required for a remote and largely asynchronous work environment
• Demonstrated capacity to clearly and concisely communicate complex technical problems and propose iterative solutions
• Experience owning a feature from concept to production, including proposal, discussion, and execution

Nice to have 

• Experience with document processing tools (AWS Textract, Azure Document Intelligence, or similar OCR/layout detection systems)
• Experience with PDF and Image processing libraries (e.g. PyMuPDF, opnecv, pillow)
• Experience in Machine Learning/ Data Science (e.g., ML algorithm selection, feature engineering, model training, hyperparameter tuning, supervised and unsupervised learning implementation, building a model pipelines, using Machine Learning tools/libraries/frameworks)
• Experience working with AWS big data technologies (Redshift, S3, EMR, Glue, etc.)

English level 

Upper-intermediate 

Legal & Hiring Information 

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel  

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

We are looking for a Senior/Lead ML Engineer to join us at Exadel. This role works closely with data scientists, software engineers, and subject matter experts in different business areas to build production systems capable of processing multi-document PDFs, with automated document type detection and field extraction at scale.

Why Join Exadel

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks.

From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

About the Client  

The leading provider of vehicle lifecycle solutions, with headquarters in Chicago, enables the companies that build, insure, and replace vehicles to power the next generation of transportation. Its platform delivers advanced mobile, artificial intelligence, and car technologies. It connects a network of 350+ insurance companies, 24,000+ repair facilities, hundreds of parts suppliers, and dozens of third-party data and service providers. The customer's collective solutions enhance productivity and help clients deliver better experiences for end consumers.

What You’ll Do

• Design and implement end-to-end document intelligence pipelines on AWS
• Develop and optimize ML models for document classification, segmentation, and field extraction
• Build scalable data processing systems handling PDFs up to 2000 pages
• Collaborate with subject matter experts to create and refine requirements for extraction
• Own features from research through production deployment and monitoring
• Establish evaluation frameworks and quality metrics for extraction accuracy

What You Bring

• Advanced knowledge of Python (native, Pandas, ScikitLearn, Tensorflow or Pytorch, PyStats, Pydantic)
• Experience with AWS tools for ML Engineering and ML deployment (Sagemaker, Lambda, Cloudformation/CDK, Step Functions)
• Advanced knowledge of SQL and Data Modeling
• Experience with GenAI for document intelligence, including prompt engineering, RAG (Retrieval Augmented Generation), multi-modal models (vision + text), and production deployment using AWS Bedrock or Azure OpenAI APIs
• Experience in experiment design (power analysis and hypothesis testing)
• Proficiency in both written and verbal communication, required for a remote and largely asynchronous work environment
• Demonstrated capacity to clearly and concisely communicate complex technical problems and propose iterative solutions
• Experience owning a feature from concept to production, including proposal, discussion, and execution

Nice to have 

• Experience with document processing tools (AWS Textract, Azure Document Intelligence, or similar OCR/layout detection systems)
• Experience with PDF and Image processing libraries (e.g. PyMuPDF, opnecv, pillow)
• Experience in Machine Learning/ Data Science (e.g., ML algorithm selection, feature engineering, model training, hyperparameter tuning, supervised and unsupervised learning implementation, building a model pipelines, using Machine Learning tools/libraries/frameworks)
• Experience working with AWS big data technologies (Redshift, S3, EMR, Glue, etc.)

English level 

Upper-intermediate 

Legal & Hiring Information 

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel  

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

We are looking for a Senior ML Engineer to join us at Exadel. This role works closely with data scientists, software engineers, and subject matter experts in different business areas to build production systems capable of processing multi-document PDFs, with automated document type detection and field extraction at scale.

Why Join Exadel

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

About the Client 

The leading provider of vehicle lifecycle solutions, with headquarters in Chicago, enables the companies that build, insure, and replace vehicles to power the next generation of transportation. Its platform delivers advanced mobile, artificial intelligence, and car technologies. It connects a network of 350+ insurance companies, 24,000+ repair facilities, hundreds of parts suppliers, and dozens of third-party data and service providers. The customer's collective solutions enhance productivity and help clients deliver better experiences for end consumers.

What You’ll Do

• Design and implement end-to-end document intelligence pipelines on AWS
• Develop and optimize ML models for document classification,segmentation, and field extraction
• Build scalable data processing systems handling PDFs up to 2000 pages
• Collaborate with subject matter experts to create and refine requirements for extraction
• Own features from research through production deployment and monitoring
• Establish evaluation frameworks and quality metrics for extraction accuracy

What You Bring

• Advanced knowledge of Python (native, Pandas, ScikitLearn, Tensorflow or Pytorch, PyStats, Pydantic)
• Experience with AWS tools for ML Engineering and ML deployment(Sag
• emaker, Lambda, Cloudformation/CDK, Step Functions)
• Advanced knowledge of SQL and Data Modeling
• Experience with GenAI for document intelligence, including prompt engineering, RAG (Retrieval Augmented Generation), multi-modal models (vision + text), and production deployment using AWS Bedrock or Azure OpenAI APIs
• Experience in experiment design (power analysis and hypothesis testing)
• Proficiency in both written and verbal communication, required for a remote and largely asynchronous work environment
• Demonstrated capacity to clearly and concisely communicate complex technical problems and propose iterative solutions
• Experience owning a feature from concept to production, including proposal, discussion, and execution

Nice to have 

• Experience with document processing tools (AWS Textract, Azure, Document Intelligence, or similar OCR/layout detection systems)
• Experience with PDF and Image processing libraries (e.g. PyMuPDF, opnecv, pillow)
• Experience in Machine Learning/ Data Science (e.g., ML algorithm selection, feature engineering, model training, hyperparameter tuning, supervised and unsupervised learning implementation, building a model pipelines, using Machine Learning tools/libraries/frameworks)
• Experience working with AWS big data technologies (Redshift, S3, EMR, Glue, etc.)

English level 

Upper-intermediate 

Legal & Hiring Information 

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel  

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

We are looking for a Senior ML Engineer to join us at Exadel. This role works closely with data scientists, software engineers, and subject matter experts in different business areas to build production systems capable of processing multi-document PDFs, with automated document type detection and field extraction at scale.

Why Join Exadel

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

About the Client 

The leading provider of vehicle lifecycle solutions, with headquarters in Chicago, enables the companies that build, insure, and replace vehicles to power the next generation of transportation. Its platform delivers advanced mobile, artificial intelligence, and car technologies. It connects a network of 350+ insurance companies, 24,000+ repair facilities, hundreds of parts suppliers, and dozens of third-party data and service providers. The customer's collective solutions enhance productivity and help clients deliver better experiences for end consumers.

What You’ll Do

• Design and implement end-to-end document intelligence pipelines on AWS
• Develop and optimize ML models for document classification,segmentation, and field extraction
• Build scalable data processing systems handling PDFs up to 2000 pages
• Collaborate with subject matter experts to create and refine requirements for extraction
• Own features from research through production deployment and monitoring
• Establish evaluation frameworks and quality metrics for extraction accuracy

What You Bring

• Advanced knowledge of Python (native, Pandas, ScikitLearn, Tensorflow or Pytorch, PyStats, Pydantic)
• Experience with AWS tools for ML Engineering and ML deployment(Sag
• emaker, Lambda, Cloudformation/CDK, Step Functions)
• Advanced knowledge of SQL and Data Modeling
• Experience with GenAI for document intelligence, including prompt engineering, RAG (Retrieval Augmented Generation), multi-modal models (vision + text), and production deployment using AWS Bedrock or Azure OpenAI APIs
• Experience in experiment design (power analysis and hypothesis testing)
• Proficiency in both written and verbal communication, required for a remote and largely asynchronous work environment
• Demonstrated capacity to clearly and concisely communicate complex technical problems and propose iterative solutions
• Experience owning a feature from concept to production, including proposal, discussion, and execution

Nice to have 

• Experience with document processing tools (AWS Textract, Azure, Document Intelligence, or similar OCR/layout detection systems)
• Experience with PDF and Image processing libraries (e.g. PyMuPDF, opnecv, pillow)
• Experience in Machine Learning/ Data Science (e.g., ML algorithm selection, feature engineering, model training, hyperparameter tuning, supervised and unsupervised learning implementation, building a model pipelines, using Machine Learning tools/libraries/frameworks)
• Experience working with AWS big data technologies (Redshift, S3, EMR, Glue, etc.)

English level 

Upper-intermediate 

Legal & Hiring Information 

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel  

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

We are looking for a Senior ML Engineer to join us at Exadel. This role works closely with data scientists, software engineers, and subject matter experts in different business areas to build production systems capable of processing multi-document PDFs, with automated document type detection and field extraction at scale.

Why Join Exadel

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

About the Client 

The leading provider of vehicle lifecycle solutions, with headquarters in Chicago, enables the companies that build, insure, and replace vehicles to power the next generation of transportation. Its platform delivers advanced mobile, artificial intelligence, and car technologies. It connects a network of 350+ insurance companies, 24,000+ repair facilities, hundreds of parts suppliers, and dozens of third-party data and service providers. The customer's collective solutions enhance productivity and help clients deliver better experiences for end consumers.

What You’ll Do

• Design and implement end-to-end document intelligence pipelines on AWS
• Develop and optimize ML models for document classification,segmentation, and field extraction
• Build scalable data processing systems handling PDFs up to 2000 pages
• Collaborate with subject matter experts to create and refine requirements for extraction
• Own features from research through production deployment and monitoring
• Establish evaluation frameworks and quality metrics for extraction accuracy

What You Bring

• Advanced knowledge of Python (native, Pandas, ScikitLearn, Tensorflow or Pytorch, PyStats, Pydantic)
• Experience with AWS tools for ML Engineering and ML deployment(Sag
• emaker, Lambda, Cloudformation/CDK, Step Functions)
• Advanced knowledge of SQL and Data Modeling
• Experience with GenAI for document intelligence, including prompt engineering, RAG (Retrieval Augmented Generation), multi-modal models (vision + text), and production deployment using AWS Bedrock or Azure OpenAI APIs
• Experience in experiment design (power analysis and hypothesis testing)
• Proficiency in both written and verbal communication, required for a remote and largely asynchronous work environment
• Demonstrated capacity to clearly and concisely communicate complex technical problems and propose iterative solutions
• Experience owning a feature from concept to production, including proposal, discussion, and execution

Nice to have 

• Experience with document processing tools (AWS Textract, Azure, Document Intelligence, or similar OCR/layout detection systems)
• Experience with PDF and Image processing libraries (e.g. PyMuPDF, opnecv, pillow)
• Experience in Machine Learning/ Data Science (e.g., ML algorithm selection, feature engineering, model training, hyperparameter tuning, supervised and unsupervised learning implementation, building a model pipelines, using Machine Learning tools/libraries/frameworks)
• Experience working with AWS big data technologies (Redshift, S3, EMR, Glue, etc.)

English level 

Upper-intermediate 

Legal & Hiring Information 

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel  

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

We are looking for a Senior ML Engineer to join us at Exadel. This role works closely with data scientists, software engineers, and subject matter experts in different business areas to build production systems capable of processing multi-document PDFs, with automated document type detection and field extraction at scale.

Why Join Exadel

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

About the Client 

The leading provider of vehicle lifecycle solutions, with headquarters in Chicago, enables the companies that build, insure, and replace vehicles to power the next generation of transportation. Its platform delivers advanced mobile, artificial intelligence, and car technologies. It connects a network of 350+ insurance companies, 24,000+ repair facilities, hundreds of parts suppliers, and dozens of third-party data and service providers. The customer's collective solutions enhance productivity and help clients deliver better experiences for end consumers.

What You’ll Do

• Design and implement end-to-end document intelligence pipelines on AWS
• Develop and optimize ML models for document classification,segmentation, and field extraction
• Build scalable data processing systems handling PDFs up to 2000 pages
• Collaborate with subject matter experts to create and refine requirements for extraction
• Own features from research through production deployment and monitoring
• Establish evaluation frameworks and quality metrics for extraction accuracy

What You Bring

• Advanced knowledge of Python (native, Pandas, ScikitLearn, Tensorflow or Pytorch, PyStats, Pydantic)
• Experience with AWS tools for ML Engineering and ML deployment(Sag
• emaker, Lambda, Cloudformation/CDK, Step Functions)
• Advanced knowledge of SQL and Data Modeling
• Experience with GenAI for document intelligence, including prompt engineering, RAG (Retrieval Augmented Generation), multi-modal models (vision + text), and production deployment using AWS Bedrock or Azure OpenAI APIs
• Experience in experiment design (power analysis and hypothesis testing)
• Proficiency in both written and verbal communication, required for a remote and largely asynchronous work environment
• Demonstrated capacity to clearly and concisely communicate complex technical problems and propose iterative solutions
• Experience owning a feature from concept to production, including proposal, discussion, and execution

Nice to have 

• Experience with document processing tools (AWS Textract, Azure, Document Intelligence, or similar OCR/layout detection systems)
• Experience with PDF and Image processing libraries (e.g. PyMuPDF, opnecv, pillow)
• Experience in Machine Learning/ Data Science (e.g., ML algorithm selection, feature engineering, model training, hyperparameter tuning, supervised and unsupervised learning implementation, building a model pipelines, using Machine Learning tools/libraries/frameworks)
• Experience working with AWS big data technologies (Redshift, S3, EMR, Glue, etc.)

English level 

Upper-intermediate 

Legal & Hiring Information 

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel  

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Position Overview:  

As a Senior Software Engineer at Diligent, you’ll be hands-on in shaping the future of our platform by designing and delivering secure, scalable, and high-performing microservices that power our SaaS solutions. You’ll have the full power of AWS at your disposal and will work primarily in C#/.Net Core and Angular to build serverless solutions, either from the ground up or by modernizing existing services. 

In this role, you’ll lead by example, owning services end-to-end from development to deployment and monitoring, driving architectural discussions, and mentoring others across the team. You’ll be a key voice in evolving our engineering practices and will actively champion the use of AI-powered tools to streamline development, improve quality, and boost team productivity. 

We’re looking for someone who is not only passionate about building great software but also excited to explore how AI can unlock better ways of working for themselves and their teammates. 

Key Responsibilities: 

• Design and own secure, scalable services, guiding technical decisions and evaluating trade-offs (including AI-driven components) to meet reliability, performance, and cost goals.
• Leverage AI tools to accelerate coding, debugging, testing, and prototyping, while rigorously validating outputs to ensure quality and safety.
• Advise on appropriate AI use (model concepts, prompt patterns, ethical/privacy considerations), embed monitoring and compliance checks into workflows, and document residual risks and mitigations.
• Coach peers on engineering best practices and AI-augmented approaches; partner with Product, Security, DevOps, and other teams to align on features, deployment, and compliance.
• Scout and pilot emerging tools or frameworks (including AI toolchains), integrate automated governance checks into pipelines, and enhance observability and incident response with an eye on productivity, cost, and resilience. 

Required Experience/Skills  

• 5-7 years of professional software engineering in an agile environment, delivering secure, scalable services.
• Understands high-level LLM concepts (e.g., hallucinations, prompt sensitivity) and safe vs. unsafe AI use cases.
• Experienced in using AI tools to accelerate coding, debugging, testing, and prototyping, with critical review of outputs.
• Skilled in prompt engineering—designing reusable prompts and coaching peers.
• Familiar with ethical/cost risks (bias, privacy, vendor lock-in) and embeds basic compliance checks into workflows.
• Proficient in C#, .Net for RESTful APIs (OpenAPI), and hands-on AWS serverless patterns.
• Comfortable with infrastructure as code (CDK/Terraform), containerization (Docker), CI/CD pipelines, and monitoring tools.
• Experience with SQL (PostgreSQL) and/or NoSQL databases; able to design and optimize schemas for performance.
• Applies security best practices in code and deployments (e.g., IAM, secrets management) and reviews AI-assisted suggestions for safety.
• Strong communication of technical and AI-related concepts to diverse stakeholders.
• Proven ability to mentor or guide peers on engineering best practices and AI-augmented workflows.
• Familiarity with Angular to collaborate effectively on end-to-end features.
• Degree in Computer Science/Engineering/related field or equivalent hands-on experience. 

Here’s a summary of the role:   

You’re ready to work at scale — re‑thinking how data is collected, processed and delivered to our customers end‑to‑end. As a Staff Software Engineer working on a  building up a cutting edge data ecosystem, you’ll shape architectures that power feeds, analytics platforms, reports and dashboards used by customers every day. You’ll explore and apply cloud technologies, distributed systems, AI solutions, influencing technical direction while still getting hands‑on with code. This role is for you if you thrive on data pipelines, APIs, cloud‑native services, scalability, performance, and reliability, enjoy technical leadership, and want your engineering decisions to have visible impact from ingestion to insight. 

Here’s a breakdown of what you’ll do (not all of it, just the important stuff): 

• Set technical direction across teams, driving ai-native and cloud‑native architecture and long‑term system evolution 

• Lead design of secure, scalable MCP hosts, and AWS microservices, balancing performance, reliability, and cost 

• Influence AI adoption through AI first solution desing, model guidance, prompt strategy, and built‑in governance and monitoring 

• Shape roadmaps with Product, Security, and DevOps to deliver compliant, high‑impact solutions 

• Evaluate and pilot emerging technologies to boost developer productivity and platform capability 

• Mentor engineers, raising engineering standards and fostering ethical, AI‑aware practices 

These are the essentials you’ll need to get an interview: 

• Deep background in enterprise software design, implementation, and operation (OOP, commercial environments) 

• Extensive hands‑on experience with cloud native architecture and services, ideally on AWS 

• Strong foundation in data driven systems: data acquisition, processing pipelines, and customer facing reporting 

• Proven experience with delivering AI based customer solutions to production 

• Familiarity with modern data transformation tools such as dbt 

• Proven expertise with SQL and NoSQL databases, alongside APIs and microservices at scale 

• Senior engineer mindset: proactive problem solver, comfortable owning outcomes 

• Leading multiple concurrent projects and ensuring strong collaboration with a wide range of stakeholders 

• Passion for continuous improvement—sharing knowledge, refining processes, and raising the bar across teams 

• Curiosity for new tools and patterns, with a pragmatic approach to adopting what works best 

 It would be great if you had these to, but we’ll support you if you don’t: 

• Experience with TypeScript and Python in production, ideally across data‑ and service‑oriented systems 

• Hands‑on experience with PostgreSQL and strong SQL workflows 

• Exposure to cloud data platforms, especially Snowflake, at scale 

• Comfortable working across the full data lifecycle—from ingestion to analytics and reporting 

#LIHybrid

Here’s a summary of the role:  

Here’s a breakdown of what you’ll do (not all of it, just the important stuff):

• Build and maintain the GRC Brain (AI reasoning layer) and Agentic Cortex (agent orchestration framework) — the technical core of our Compliance in a Box product
• Design and implement a 7-agent architecture: OnboardingAgent, ScopeAgent, StandardsMapper, RiskQuantifier, PolicyAnalyzer, InfrastructureAuditor, and ComplianceMonitor
• Implement Human-in-the-Loop (HITL) gates across agent workflows, and tune prompts and confidence scoring for Bedrock-hosted models
• Own the agent evaluation framework — measuring quality, latency, and reliability to keep CiaB performant and production-ready
• Collaborate with cross-functional teams to deliver CiaB feature-complete by Week 7 — your work ships fast and your impact is visible from day one

These are the essentials you’ll need to get an interview:

• A degree in Computer Science, Software Engineering, or a related IT discipline
• Demonstrable understanding of AI/ML concepts, including LLMs and agent-based systems
• Ability to write clean, well-tested code — Python preferred
• Strong experience of shipping real AI products - not chatbots!
• Strong communication skills and a collaborative mindset

It would be great if you had these to, but we’ll support you if you don’t:

• Exposure to AWS services, especially Amazon Bedrock or similar LLM hosting platforms
• Familiarity with GRC concepts (governance, risk, compliance) or cybersecurity frameworks such as ISO 27001 or SOC 2
• Any experience with agent orchestration libraries (e.g. LangChain, CrewAI, AutoGen)

This role is located in Budapest, Hungary — We are a hybrid work environment and are in the office 3+ days/week.

Tulip, the leader in AI-native frontline operations, is helping companies around the world equip their workforce with composable, connected apps, leading to higher quality work, improved efficiency, and end-to-end traceability across operations. Tulip's cloud-native, no-code platform, powered by embedded AI, is driving the digital transformation of industrial environments through composable, human-centric solutions that go beyond disrupting the Manufacturing Execution System (MES) category.

A spinoff out of MIT, Tulip is headquartered in Somerville, MA, with offices in Germany, Hungary, Singapore, and Israel. Tulip has been recognized as a World Economic Forum Global Innovator, a 2024 Deloitte Technology Fast award winner, one of Energage's Top Workplaces USA, and one of Built In Boston's "Best Places to Work" and "Best Midsize Places to Work."

About You:

This role represents a strategic merger between the Tulip Library and the Tulip Experience Center (TEC). As an Ecosystem & Low-Code Developer, you will architect composable assets and demo environments that showcase the platform's power to prospective clients. You lead the charge in AI transformation — designing the user journey for a world where Tulip builders use AI to create solutions — and own the full development lifecycle from scoping to commercial enablement.

What skills do I need?

• 2+ years of experience in solution engineering, content creation, or technical development
• Hands-on AI proficiency — you've built repeatable workflows, prompt libraries, and templates that save time and improve output quality
• Strong technical aptitude with a data-driven mindset and basic programming knowledge
• Excellent English communication skills, with the ability to translate complex technical features into clear, benefit-driven language
• Nice to have: Interest in UX/service design, AI tools, or MCP servers
• Nice to have: Genuine curiosity and empathy for manufacturing processes and frontline operations
• Relevant degree in Engineering (Process, Industrial, Mechanical) or Design (Product, Industrial), or equivalent working experience

Key Responsibilities: 

• Develop and maintain a high-quality catalog of pre-built applications, API connectors, and custom UI widgets to drive rapid platform adoption across the Tulip Library
• Design and test AI-centric user journeys that help Tulip builders create solutions faster and more effectively, moving from personal AI use to team-level impact
• Manage the end-to-end development lifecycle of Library assets — from concept scoping and technical architecture to testing and quality assurance across diverse customer environments
• Architect and implement standard demo environments that communicate the value of Tulip, specifically highlighting how AI can transform frontline operations for prospective clients
• Build internal tools, prompt libraries, and playbooks that reduce ramp time for new builders and establish the standard for AI-integrated manufacturing workflows
• Write comprehensive technical guides and produce walkthrough videos; collaborate with Product, Marketing, and Sales teams to ensure all content aligns with company positioning and enables commercial success

Key Collaborators:

• Product and Engineering Team — provide direct feedback on platform capabilities and collaborate on integrating new features, especially AI tools
• Product Marketing Team — ensure Library content and demos align with company messaging and the vision of an AI-augmented workforce
• Sales and Presales Teams — build high-impact demos and enable internal teams to use developed tools and AI workflows effectively
• Customer Success & Education — provide materials that support customer onboarding and long-term success

Working At Tulip

We know even great candidates experience imposter syndrome. Even if you don't match every requirement, applying gives you the opportunity to be considered. We're building a strong, diverse team that values hard work, families, and personal well-being.

Benefits of working with us include:

• Direct impact on product and culture
• Private Healthcare insurance
• Company equity
• Virtual company events and happy hours
• Flexible work schedule and unlimited vacation policy
• Team Lunches in KFT Hub and office snacks
• Learning & Development benefits
• HU Eyeglass Benefit
• An inclusive, dog-friendly office with diverse and inspiring colleagues

We are an equal opportunity employer. At Tulip, we celebrate all. Qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Help us build an inclusive community that will transform frontline operations.

Please note that we may use AI-based tools to support parts of our hiring process. All data processing is carried out in compliance with local data protection laws, ensuring all personal candidate information is handled securely and ethically.

Position Overview:

We are seeking a talented and driven Senior Software Engineer in AI to join our growing team at Diligent. Reporting to Applied Science Manager, this exciting role involves bridging the gap between Applied Scientists and Product teams - developing, deploying, and scaling ML and LLM-based systems as part of Diligent’s AI platform services to accelerate AI adoption across Diligent's diverse product suite. 

Diligent is a global leader in modern governance, delivering innovative SaaS solutions that address governance, risk, and compliance (GRC) needs. Our mission is to empower leaders with cutting-edge technology, actionable insights, and vital connections to drive impactful decisions and lead with purpose. 

Key Responsibilities: 

• Design, develop, deploy, monitor, scale, and troubleshoot ML and LLM-based systems that power services across our platform. 

• Build automated AI testing and evaluation frameworks. 

• Collaborate with Applied Scientists and Software Engineers to implement and productize AI-based capabilities. 

• Shape and develop the teams AI platform infrastructure utilizing already established patterns at the organization. 

• Design and develop AI libraries and frameworks to help accelerate value delivery across AI platform services. 

• Work on projects involving sensitive customer content used for Diligent customers’ board communications, which requires stringent privacy and security measures.  

• Document and communicate your approach, progress, and results to the broader team and to other development teams. 

Required experience/skills: 

• 5+ years of relevant experience. 

• Strong ability to develop highly readable and well-tested code that adheres to SOLID principles. 

• Proven proficiency in Python and TypeScript. 

• Experience with infrastructure-as-code practices preferably in AWS (or experience with other major cloud providers). 

• Ability to contribute to a high-performing agile team, and to product innovation. 

• Keen to improve processes and share knowledge across the team. 

Nice to have:  

• Hands-on AWS CDK experience 

• Hands-on experience with LLMs including prompt engineering, fine-tuning, model evaluation, RAG, agentic solutions or MCP servers. 

• Experience with full AI-based solution lifecycle.

#LI-Hybrid

Position Overview:  

As a Staff Software Engineer at Diligent, you’ll create robust, scalable, and secure microservices that power our SaaS platform for governance. You’ll leverage AWS (serverless or migrations) with TypeScript, own services end-to-end (code, deployment, monitoring), drive architecture discussions, and regularly demo to the department. A critical part of this role is shaping our AI strategy: you’ll lead design decisions, embed AI responsibly into systems, and mentor teams on AI capabilities, safety, and governance. 

Key Responsibilities: 

• Champion the design and delivery of secure, high-performance microservices on AWS, driving architecture decisions and empowering team members through mentorship.
• Set technical direction across multiple teams, spotting system pain points and proposing improvements.
• Pioneer AI-driven solutions by advising on model capabilities, crafting effective prompt strategies, and embedding governance and monitoring into development workflows.
• Partner with Product, Security, and DevOps to shape technical roadmaps, ensure compliance, and seamlessly integrate AI features that deliver real business value.
• Continuously elevate our toolkit by evaluating and piloting cutting-edge technologies (including AI toolchains), optimizing for performance, cost efficiency, and developer productivity.
• Own projects end-to-end—from ideation and prototyping to deployment, monitoring, and iteration—ensuring resilient, maintainable systems and top-notch code quality.
• Mentor engineers in best practices and AI-augmented workflows, fostering a culture of experimentation, learning, and ethical AI adoption.
• Stay ahead of emerging AI trends and regulations, proactively adapting designs and practices to meet evolving standards and steer future innovation. 

Required Experience/Skills  

• 7–10 years delivering secure, scalable applications in agile environments.
• Understanding of model architectures (e.g., transformer vs. retrieval-augmented), bias and safety concerns, prompt engineering, and proven experience shaping AI strategy and mentoring teams on responsible AI use. Ability to architect AI systems with embedded monitoring and governance.
• Design and review scalable, high-performance system architectures, APIs, and data models, while writing high-quality, testable code in Node.js, React, and TypeScript/JavaScript, including reusable libraries and frameworks.
• Lead end-to-end DevOps and platform engineering, including CI/CD pipeline design with strong guardrails, infrastructure-as-code and modern deployment strategies, cloud observability and incident response, and cost-aware architecture and capacity planning across AWS, Azure, and GCP
• Integrates security best practices (IAM, secrets management) into all work, including AI components, and embeds bias/privacy checks in delivery pipelines.
• Strong communication of technical and AI-related concepts to diverse stakeholders; proven ability to lead projects, influence engineering culture, and mentor peers in AI-augmented workflows.
• Degree in Computer Science, Engineering, Mathematics, or equivalent experience.