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. 

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

• You've built production data models and know how to turn vague business questions into clear, canonical definitions
• You use AI tooling as your primary mode of engineering and have developed a real point of view on how to deliver high-quality datasets when the technical work is done by AI
• You're comfortable engaging with stakeholders to untangle what they actually need and turning that conversation into a structured analytical approach
• You're looking for a role where agentic tools are the default, and where you can help shape how a central data team delivers the reliable signals that operational and strategic decisions depend on.

What Skills Do I Need?

• Bachelor's degree in a quantitative, technical, or business field, or equivalent working experience.
• 4+ years of experience in analytics, data science, or data engineering, with increasing scope and ownership.
• Proficiency with agentic coding tools (e.g., Claude Code, Cursor) as your primary mode of building, testing, and documenting production data models, including shipping reusable assets that improve agentic workflows.
• Experience translating business requirements into structured analytical approaches, running workshops, and aligning stakeholders on canonical metric definitions.
• Strong data modeling skills and the ability to write performant SQL against cloud warehouses, with a strong emphasis on data quality and automated testing.
• SQL and Python proficiency for data modeling, pipeline orchestration, and API integrations using the broader data stack (dbt, Airflow, dlt, etc.).

Nice to Haves

• Experience with semantic modeling tools such as MetricFlow, Cube, or LookML
• Experience with data cataloging and metadata platforms such as DataHub or Atlan
• Familiarity with BI tools such as Tableau, Looker, or Sigma

Key Responsibilities

• Build and maintain data models and pipelines primarily using AI coding tools, with consistent best-practice patterns, clear documentation, and high-quality standards
• Build and improve agentic coding workflows to accelerate data modeling and testing, while staying in the loop on business logic, review, and company-specific edge cases
• Partner with stakeholders to surface conflicting metric definitions, run alignment workshops, and establish canonical standards across domains
• Define and enforce data quality standards across pipelines — including unit tests grounded in sample data and lineage-aware test placement — and enable domain analysts to follow the same standards
• Prototype and iterate on a semantic and context layer that makes Tulip's data accessible to both analysts and AI agents, including the documentation and instructions that let an LLM behave correctly against it
• Help the team make sensible calls about where on the risk curve to deploy AI: lower-risk for internal modeling and testing, more cautious for self-serve BI, and most cautious for anything customer-facing

Key Collaborators

• Commercial Teams
• Marketing Teams
• Product and Engineering Teams
• Operational Leadership
• Data Analytics stakeholders across departments

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.

About the Role

Diligent is the AI leader in GRC solutions, helping organizations around the world turn governance, risk, compliance, audit, and ESG into a competitive advantage. Within HR we're embarking on our own transformation journey to fundamentally redesign how our people experience HR at Diligent.

We're looking for a AI Systems & Data Engineer who can co-own the technical heavy lifting of this transformation. This isn't just configuration work — you'll write Python scripts for complex data conversions, build AI agents and standalone people-facing solutions, architect integrations, design automation workflows, and solve problems we haven't encountered yet.

We need a strong engineer who can figure things out, move fast, and think about the impact on thousands of people, not just data rows—someone who cares about impact, not just technically elegant solutions. You'll have the autonomy to propose ideas, experiment, and own outcomes, while working with experienced HR and technology teams who can provide context and support.

Key Responsibilities

• Play a key role in the data migration workstream from Oracle HCM and Greenhouse to Workday — writing Python scripts for complex data transformations, conducting manual data audits to validate integrity, and building automated validation frameworks.
• Design and build a modern AI-powered automated acceptance testing framework for the Workday implementation — enabling the team to run rigorous, repeatable UAT without manual overhead.
• Design and build scalable workflow automations across the HR tech stack, using Workato and other platforms.
• Build conversational AI agents and standalone AI-powered solutions (e.g. self-service People Experience tools) on DiligentGPT (Glean), Workato, self-hosted, and other platforms — including hosted tools with their own presence beyond a single chat interface.
• Build AI-powered auditing and validation agents to monitor data integrity, flag anomalies, and surface quality issues across HR systems — with AI layer exploration.
• Support implementation and configuration of HR tooling and integrations across the tech stack, ensuring systems are properly connected and maintained.
• Create data visualisations and dashboards that enable HR stakeholders to access insights, make data-driven decisions, and identify opportunities for automation — while also monitoring migration progress and system health.
• Document technical architecture, data flows, and integration patterns to enable future maintenance and support knowledge transfer.
• Troubleshoot and resolve data quality issues, integration failures, and system errors as they arise during implementation and post-go-live.
• Partner with HR Operations, HRIS, and business stakeholders to gather technical requirements and translate business needs into technical solutions.
• Question assumptions, propose better approaches, and advocate for solutions that are technically sound and human-centred.

Required Skills & Experience

• 4+ years of hands-on engineering experience building data pipelines, integrations, or automation systems
• Strong Python skills with experience in complex data transformations and clean, maintainable code
• Experience with APIs (REST, SOAP), JSON, XML and integrating different systems; comfortable with SQL and database concepts
• Experience with automation/integration platforms (e.g. Workato, JSM) and AI agents, chatbots, or LLM-powered applications
• Familiarity with enterprise HRIS platforms (Workday, Oracle HCM) and understanding of HR data structures
• Proven track record of leading technical projects end-to-end with stakeholder management and delivery ownership
• Self-directed and outcome-focused — you figure things out, communicate technical concepts clearly, and care about solving problems

What You'll Gain

• Understanding of how HR transformation works at scale across a global organization.
• Deep hands-on experience with Workday (industry-leading HRIS) implementation and configuration
• AI agent development and LLM integration experience building production tools used by thousands of employees
• Enterprise data migration and integration architecture expertise across complex HR systems
• Automation platform mastery and workflow design skills
• Exposure to the intersection of people, process, technology, and change management while building relationships across HR, IT, Data, and Apps teams
• Portfolio-worthy work: AI agents, data pipelines, and integrations used by 2,500+ employees across 21 countries
• Experience that translates to HR tech consulting, product engineering, or senior IC/leadership roles

This is a one year fixed-term role (possibility to move to permanent) tied to our Workday implementation and AI transformation roadmap. You'll report to the Senior Director of HR AI & Systems Transformation (who is based in London) and work closely with our global team across HR Operations, HRIS, IT, Data, Apps, and transformation project teams.

#LI-Hybrid

Technologists at WorldQuant research, design, code, test and deploy firmwide platforms and tooling while working collaboratively with researchers and portfolio managers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people.

The Role: WorldQuant is seeking an exceptional candidate to join the firm as a Quantitative Developer. The right candidate will be able to use their development and practical thinking skills to slice through complicated challenges to find the most clear and effective solutions. Quant Developers will design, code and implement proprietary systems and tools to help bring research ideas to life, and have a real business impact. You will collaborate with Quant Researchers and Portfolio Managers, data scientists, mathematicians and computer scientists to gather, analyze and spec out requirements, develop and test code, and manage deliverables. A successful candidate will have a track record of solving problems, be comfortable thinking outside the box, and bring cross-disciplinary solutions into play
  
What You’ll Bring:

• 2+ years of hands-on experience as a developer
• Background in Computer Science, Engineering, or related discipline 
• Strong computer science fundamentals - algorithms, design patterns, OOP, threading, multiprocessing, etc. - Data Structure and Algorithms are the most important fundamentals in need, etc.
• Clean and Concise coding style
• Demonstrate mastery of any programming language. Python is best, or C++ is great, others are fine
• Experience working in Linux environments is a huge plus
• Experience building distributed or data intensive systems is a big plus
• Demonstrated problem solving abilities, insight, and judgment as well as a strong attention to detail
• Strong communication skills; ability to express complex concepts in simple terms, especially to non-experts
• Understanding of basic probability, statistical inference, software solvers, mathematical optimization is a plus, but not essential
• Interest and experience in LLM, agentic systems is a plus, but not essential

What We Offer:

• Competitive compensation package 
• Core benefits include: premium private health insurance and life insurance with savings plan  
• Support for every aspect of life through Employee Assistance Program and fully covered sick leave 
• Strong culture of learning and development: training courses, library, guest speakers, share and learn events, global conferences 
• Regular offsite team buildings, annual conferences and occasional global summits – opportunity to travel and connect with our local and global teams.

#LI-MH1

Technologists at WorldQuant research, design, code, test and deploy firmwide platforms and tooling while working collaboratively with researchers and portfolio managers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people.

The Role We are seeking an exceptional Python Lead Engineer to join a small team working on complex data pipelines, AI/ML systems, and cutting-edge software solutions. This role will be responsible for managing technical objectives, providing technical leadership, and maintaining a hands-on approach to development. The ideal candidate will work closely across teams within WorldQuant as part of our business-facing technology organization. 
A successful candidate will possess deep expertise in Python development, data engineering, software architecture, and design principles. They should be able to mentor junior team members, conduct code reviews, and drive architectural decisions. Experience with AI and large language models (LLMs) is highly desirable.

What You'll Bring

• Master's degree or higher in Computer Science, Engineering, or a related technical field from a top-tier institution. 
• 7+ years of experience as a Python developer, with a strong focus on data engineering and AI/ML systems.
• Expert-level knowledge of Python and its ecosystem, including experience with data processing libraries like Pandas, NumPy, and PySpark. 
• Proficiency in designing and implementing scalable, maintainable, and efficient data pipelines. 
• Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes). 
• Expertise in version control systems (Git), CI/CD practices, and agile methodologies. 
• Strong communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders. 
• Proven track record of mentoring junior engineers and fostering a collaborative team environment. 
• Experience in the finance industry is a plus but not required. 
• Experience with AI/ML frameworks such as PyTorch, or scikit-learn, LLM, agents or systems of agents is a significant plus.

What We Offer:

• Competitive compensation package 
• Core benefits include: premium private health insurance and life insurance with savings plan  
• Support for every aspect of life through Employee Assistance Program and fully covered sick leave 
• Strong culture of learning and development: training courses, library, guest speakers, share and learn events, global conferences 
• Regular offsite team buildings, annual conferences and occasional global summits – opportunity to travel and connect with our local and global teams 

Technologists at WorldQuant research, design, code, test and deploy firmwide platforms and tooling while working collaboratively with researchers and portfolio managers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people.

The Role We are seeking an exceptional senior-level Python engineer to join a small team working on complex data pipelines, AI/ML systems, and cutting-edge software solutions. This role will be responsible for managing technical objectives, providing technical leadership, and maintaining a hands-on approach to development. The ideal candidate will work closely across teams within WorldQuant as part of our business-facing technology organization.
A successful candidate will possess deep expertise in Python development, data engineering, software architecture, and design principles. They should be able to mentor junior team members, conduct code reviews, and drive architectural decisions. Experience with AI and large language models (LLMs) is highly desirable.

What You'll Bring

• Master's degree or higher in Computer Science, Engineering, or a related technical field from a top-tier institution. 
• 5+ years of experience as a Python developer, with a strong focus on data engineering and AI/ML systems.
• Expert-level knowledge of Python and its ecosystem, including experience with data processing libraries like Pandas, NumPy, and PySpark. 
• Proficiency in designing and implementing scalable, maintainable, and efficient data pipelines. 
• Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes). 
• Expertise in version control systems (Git), CI/CD practices, and agile methodologies. 
• Strong communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders. 
• Experience in the finance industry is a plus but not required. 
• Experience with AI/ML frameworks such as PyTorch, or scikit-learn, LLM, agents or systems of agents is a significant plus.

What We Offer:

• Competitive compensation package 
• Core benefits include: premium private health insurance and life insurance with savings plan  
• Support for every aspect of life through Employee Assistance Program and fully covered sick leave 
• Strong culture of learning and development: training courses, library, guest speakers, share and learn events, global conferences 
• Regular offsite team buildings, annual conferences and occasional global summits – opportunity to travel and connect with our local and global teams 

About the role:

ABBYY Vantage is our flagship Document AI platform – a cloud-native, microservices-based product that combines purpose-built AI, OCR, NLP, and direct LLM integration to help enterprise customers extract, classify, and act on data from any document. Vantage 3.0, our latest release, introduces native Azure OpenAI integration, enterprise-grade compliance and redaction, a real-time analytics dashboard, and a growing library of pre-configured AI skills. Over 10,000 customers trust ABBYY – including Fortune 500 companies like DHL, Johnson & Johnson, FDA, PwC, KeyBank, Spotify, and H&R Block – to automate their most complex document workflows.

We are looking for a Staff Software Engineer to serve as a senior technical leader on the Vantage platform. You will drive the design and delivery of complex, cross-cutting capabilities – spanning document AI pipelines, LLM integrations, compliance infrastructure, analytics, and platform extensibility. Beyond your own code, you will act as a technical multiplier: influencing architectural decisions, setting quality standards, and developing the engineers around you. This is a role for someone who leads through depth, judgment, and impact.

Job Responsibilities:

• Technical Leadership: Drive the technical design and delivery of significant Vantage platform capabilities, from architecture and API contracts through deployment, monitoring, and iteration.
• Quality & Standards: Define and uphold engineering standards for the Vantage codebase – covering code quality, service reliability, performance, security, and compliance – and drive their adoption across teams.
• Strategic Collaboration: Act as a senior technical voice in cross-functional planning with product management, ML engineering, cloud architecture, and engineering leadership; translate business priorities into actionable technical roadmaps.
• Platform Improvement: Lead initiatives to improve Vantage platform health at scale: service decomposition, observability, CI/CD maturity, and developer productivity.
• Operational Excellence: Own high-severity incident response for Vantage cloud services; drive post-mortems and systemic reliability improvements.
• Engineering Mentorship: Mentor Senior and Principal Engineers on the Vantage team; build a culture of technical rigor, shared ownership, and continuous learning.
• Technical Innovation: Evaluate and champion adoption of new technologies – from GenAI model integrations to cloud-native tooling – that strengthen ABBYY's Document AI differentiation.

Job Requirements:

• 10–13 years of professional software engineering experience with deep expertise in C# .NET and C++, willing to work with both languages
• Proven experience designing, implementing, and operating CI/CD pipelines for building, testing, and deploying workflows using GitHub Actions and/or Azure DevOps Pipelines
• Strong command of microservices architecture, distributed system design, and cloud-native patterns at enterprise scale
• Demonstrated ability to mentor Senior and Mid-level Engineers and partner with Engineering Managers on technical direction
• Experience leading technical design reviews and influencing architectural decisions across team and product boundaries

Desired Qualifications

• Experience in cloud, preferably using Microsoft Azure (AKS, Storage, Key Vaults, Azure SQL or equivalent)
• Track record of delivering production-grade systems that meet enterprise compliance, security, and reliability standards
• Hands-on experience designing and operating workflow-driven systems (orchestration, retries, timeouts, and state management)
• Experience integrating Machine Learning, Neural Networks or LLMs into enterprise applications and workflows
• Comfort operating across a globally distributed engineering organization spanning multiple regions and cultures

Here are some of our local benefits:

About the role:

ABBYY Vantage is our flagship Document AI platform – a cloud-native, microservices-based product that combines purpose-built AI, OCR, NLP, and direct LLM integration to help enterprise customers extract, classify, and act on data from any document. Vantage 3.0, our latest release, introduces native Azure OpenAI integration, enterprise-grade compliance and redaction, a real-time analytics dashboard, and a growing library of pre-configured AI skills. Over 10,000 customers trust ABBYY – including Fortune 500 companies like DHL, Johnson & Johnson, FDA, PwC, KeyBank, Spotify, and H&R Block – to automate their most complex document workflows.

We are looking for a Senior Software Engineer to join the Vantage engineering team. You will be a hands-on contributor building and evolving the services that power Vantage's document AI capabilities – from OCR pipelines and skill training workflows to API integrations and analytics infrastructure. You bring strong engineering fundamentals, a quality-first mindset, and a drive to deliver reliable, scalable software in a cloud-native environment.

Job Responsibilities:

• End-to-End Development: Design, develop, test, and deploy features and services within the Vantage platform, contributing to areas such as document processing pipelines, AI skill management, cloud infrastructure, and API layers.
• Code Quality: Write clean, maintainable, well-tested code; actively participate in code reviews and champion engineering best practices across your team.
• Cross-Functional Collaboration: Work closely with product managers, UX designers, ML engineers, and fellow software engineers to translate Vantage feature requirements into well-architected solutions.
• Continuous Improvement: Identify and surface improvements to existing Vantage services, tooling, and delivery workflows; contribute to reducing technical debt and increasing engineering velocity.
• System Reliability: Monitor the health and performance of Vantage cloud services; investigate and resolve production incidents in a timely manner.
• Technical Growth: Stay current with advances in Document AI, cloud-native patterns, and GenAI integration approaches that could enhance the Vantage platform.

Job Requirements:

• 5–9 years of professional software engineering experience with deep expertise in C# .NET and C++, willing to work with both languages
• Proven experience designing, implementing, and operating CI/CD pipelines for building, testing, and deploying workflows using GitHub Actions and/or Azure DevOps Pipelines
• Good understanding of microservices architecture, distributed system design, and cloud-native patterns at enterprise scale
• Demonstrated track record of delivering high-quality, testable code
• Strong analytical and debugging skills with the ability to investigate complex issues across distributed systems

Desired Qualifications

• Experience in cloud, preferably using Microsoft Azure (AKS, Storage, Key Vaults, Azure SQL or equivalent)
• Hands-on experience designing and operating workflow-driven systems (orchestration, retries, timeouts, and state management)
• Experience integrating Machine Learning, Neural Networks or LLMs into enterprise applications and workflows
• Familiarity with OCR, NLP and computer vision technologies
• Comfort operating across a globally distributed engineering organization spanning multiple regions and cultures

Here are some of our local benefits:

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)

Here’s a summary of the role:   

You’ll use your applied machine learning and generative AI skills to design and ship LLM powered product experiences that solve real problems for real users. You turn messy documents and complex language into smart assistants, agentic solutions, and search experiences that feel fast, reliable, and trustworthy. 

In this role you work end-to-end: framing problems, shaping prompts and workflows, orchestrating tools and retrieval, and partnering with engineers and product managers to bring modern AI into production. If you enjoy building with large language models and care deeply about evaluation, safety, and impact, you’ll feel at home here. 

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

• Design, prototype, and refine LLM based features over large document sets. 

• Orchestrate multistep, agentic workflows and tool calling (including MCP servers and other integrations) so LLMs can take meaningful actions, not just generate text. 

• Define evaluation frameworks, experiments, and metrics so you can measure model quality, relevance, and safety with confidence. 

• Use AWS services (i.e. AWS Bedrock) to deliver reliable, secure, and scalable AI capabilities. 

• Work closely with domain experts, PMs and software engineers to turn prototypes into reliable, production ready services. 

• Handle complex, domain specific text (e.g. legal, financial, or regulatory content) with a strong focus on accuracy, robustness, and privacy. 

• Communicate your findings clearly, share best practices, and stay up to date with the latest ML and AI research that can improve your solutions. 

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

• Hands-on experience building LLM powered applications or features (for example RAG systems, chatbots, assistants, agentic solutions or document centric workflows) — not just using chat interfaces. 

• Strong Python skills and everyday comfort with the modern data / AI ecosystem (e.g. pandas, NumPy, basic ML libraries, HTTP APIs, and SDKs for cloud AI services). 

• Practical experience with LLM powered solution design, evaluation, and iteration: you know how to test, compare approaches, and choose the one that works best with real data. 

• Familiarity with at least one cloud platform (ideally AWS) and building or contributing to services or pipelines that run in production. 

• A degree in Computer Science, Data/Applied Science, Mathematics, Statistics, or a related technical field, or equivalent practical experience. 
  
• Clear communication skills, collaborative mindset, and a genuine interest in learning, sharing knowledge, and iterating quickly based on feedback. 

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

• Experience designing and implementing agentic workflows (multistep reasoning, tool calling, planners) and/or building MCP servers or similar tool integrations. 

• Hands-on experience with AWS Bedrock or comparable platforms (model selection, configuration, guardrails, evaluation, and cost/performance trade-offs). 

• Experience with semantic search, vector databases, and information retrieval techniques in production systems. 

• Familiarity with observability and evaluation for LLM applications (e.g. logging, feedback loops, offline and online evaluation, safety checks). 

• Experience working with complex or regulated content such as legal, risk, compliance, financial, or governance documents. 

#LI-Hybrid

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

Here’s a summary of the role:   

This is a principal-level role for someone who has already operated at Staff or Principal Engineer level in a sizeable engineering organization and can point to specific platform decisions — in production today — that they own. You'll set the technical direction for our AI-enabled platform: architecting secure, scalable, serverless systems on AWS, defining the patterns and governance practices that multiple teams adopt, and guiding where AI genuinely adds value across the stack. 

Your leverage comes from the systems, architectures, and standards you put in place — not from individual output. You'll mentor senior engineers, lead org-wide design decisions, and be the person other technical leaders turn to when the hard calls need to be made. You'll still write code, but that's not where your impact is measured. 

If you've led complex platform or AI initiatives at scale, have strong opinions about AI governance in production systems, and want the scope to shape an entire platform's future, this is that role. 

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

• Shape engineering strategy with broad organizational impact — you'll influence long-term architectural direction across multiple teams and products, not just within your own squad. 

• Drive platform evolution by identifying cross-cutting pain points and leading the design of secure, scalable, reusable solutions built on AWS and modern serverless and microservice patterns. 

• Lead architectural discussions and design reviews where the stakes are real — making clear trade-offs around performance, security, reliability, and maintainability, and getting alignment across teams with competing priorities. 

• Own AI architectural decisions end-to-end: design AI-enabled systems with built-in governance, monitoring, and regulatory readiness baked in from the start, not retrofitted. Define where AI adds genuine value and where it doesn't. 

• Act as the organization's AI thought leader — educate engineering teams on model behavior, agentic systems, and responsible AI practices, and raise the overall maturity of how we design and deploy AI. 

• Mentor and stretch senior and staff engineers, building technical leadership depth across the organisation and holding a high bar for engineering standards. 

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

• Principal-level track record at scale. 10+ years of software engineering experience, including at least 3 years' operating at Staff or Principal Engineer level in an organization of 100+ engineers. You've led large, complex platform or AI initiatives where you were the decision-maker, not a contributor. 

• Deep, opinionated AWS platform expertise. You've designed multi-account AWS architectures and made the call on when serverless is the wrong choice. You work fluently with Infrastructure as Code — Terraform or CDK preferred — and have strong views on observability, resilience, and security that you've translated into org-wide patterns. 

• Production AI systems experience. You've shipped AI-enabled systems — RAG pipelines, agentic frameworks, LLM orchestration, or similar — into production and can discuss the architectural decisions, failure modes, and trade-offs involved. "Understanding AI concepts" is not enough; we need someone who has built and run these systems. 

• AI governance in practice. You've defined and implemented AI governance in real production environments — bias and privacy checks in pipelines, audit-ready monitoring, AI usage policies — not just read about it. This is essential, not a bonus. 

• API design and backend platform delivery. Proven track record designing and shipping RESTful APIs and backend platform components using Node.js/TypeScript. You understand frontend concerns well enough to set API contracts that serve product teams effectively, even if you're not writing React day-to-day. 

• Org-level communication and influence. You can align stakeholders on complex technical decisions, run architecture forums, and mentor other senior technical leaders. You're as comfortable in a board-level conversation as you are in a design review. 

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

• Experience building platform components or SDKs that multiple product teams depend on, including the documentation and enablement work that makes them adoptable. 

• Involvement in architecture forums, tech councils, or similar bodies that define org-wide standards — either running them or playing a leading role. 

• Experience optimising cost and performance for data and AI-heavy workloads at scale, including capacity planning and infrastructure tuning. 

• Leadership of major modernisation efforts — legacy migration to serverless, multi-region architecture, or platform consolidation across product lines. 

• A public technical presence — conference talks, open-source contributions, published writing — that demonstrates thought leadership beyond your current organisation. 
  
  #LI-Hybrid
  #LI-Hybrid

Here’s a summary of the role:   

This is a principal-level role for someone who has already operated at Staff or Principal Engineer level in a sizeable engineering organization and can point to specific platform decisions — in production today — that they own. You'll set the technical direction for our AI-enabled platform: architecting secure, scalable, serverless systems on AWS, defining the patterns and governance practices that multiple teams adopt, and guiding where AI genuinely adds value across the stack. 

Your leverage comes from the systems, architectures, and standards you put in place — not from individual output. You'll mentor senior engineers, lead org-wide design decisions, and be the person other technical leaders turn to when the hard calls need to be made. You'll still write code, but that's not where your impact is measured. 

If you've led complex platform or AI initiatives at scale, have strong opinions about AI governance in production systems, and want the scope to shape an entire platform's future, this is that role. 

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

• Shape engineering strategy with broad organizational impact — you'll influence long-term architectural direction across multiple teams and products, not just within your own squad. 

• Drive platform evolution by identifying cross-cutting pain points and leading the design of secure, scalable, reusable solutions built on AWS and modern serverless and microservice patterns. 

• Lead architectural discussions and design reviews where the stakes are real — making clear trade-offs around performance, security, reliability, and maintainability, and getting alignment across teams with competing priorities. 

• Own AI architectural decisions end-to-end: design AI-enabled systems with built-in governance, monitoring, and regulatory readiness baked in from the start, not retrofitted. Define where AI adds genuine value and where it doesn't. 

• Act as the organization's AI thought leader — educate engineering teams on model behavior, agentic systems, and responsible AI practices, and raise the overall maturity of how we design and deploy AI. 

• Mentor and stretch senior and staff engineers, building technical leadership depth across the organisation and holding a high bar for engineering standards. 

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

• Principal-level track record at scale. 10+ years of software engineering experience, including at least 3 years' operating at Staff or Principal Engineer level in an organization of 100+ engineers. You've led large, complex platform or AI initiatives where you were the decision-maker, not a contributor. 

• Deep, opinionated AWS platform expertise. You've designed multi-account AWS architectures and made the call on when serverless is the wrong choice. You work fluently with Infrastructure as Code — Terraform or CDK preferred — and have strong views on observability, resilience, and security that you've translated into org-wide patterns. 

• Production AI systems experience. You've shipped AI-enabled systems — RAG pipelines, agentic frameworks, LLM orchestration, or similar — into production and can discuss the architectural decisions, failure modes, and trade-offs involved. "Understanding AI concepts" is not enough; we need someone who has built and run these systems. 

• AI governance in practice. You've defined and implemented AI governance in real production environments — bias and privacy checks in pipelines, audit-ready monitoring, AI usage policies — not just read about it. This is essential, not a bonus. 

• API design and backend platform delivery. Proven track record designing and shipping RESTful APIs and backend platform components using Node.js/TypeScript. You understand frontend concerns well enough to set API contracts that serve product teams effectively, even if you're not writing React day-to-day. 

• Org-level communication and influence. You can align stakeholders on complex technical decisions, run architecture forums, and mentor other senior technical leaders. You're as comfortable in a board-level conversation as you are in a design review. 

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

• Experience building platform components or SDKs that multiple product teams depend on, including the documentation and enablement work that makes them adoptable. 

• Involvement in architecture forums, tech councils, or similar bodies that define org-wide standards — either running them or playing a leading role. 

• Experience optimising cost and performance for data and AI-heavy workloads at scale, including capacity planning and infrastructure tuning. 

• Leadership of major modernisation efforts — legacy migration to serverless, multi-region architecture, or platform consolidation across product lines. 

• A public technical presence — conference talks, open-source contributions, published writing — that demonstrates thought leadership beyond your current organisation. 
  
  #LI-Hybrid