Senior Python / Agentic AI Engineer Capco: Where Innovation Meets Opportunity Capco is a global leader in consulting, uniquely positioned to drive innovation and transformation in the financial services industry. More than consultants, we are strategic partners and problem solvers for some of the largest organizations in Banking, Insurance, Investment Management, Data/Digital Transformation, Regulatory Compliance, and ICT Risk. Our business and technology professionals thrive in a dynamic environment where creativity, collaboration, and cutting-edge solutions are at the heart of everything we do. Experience the Capco difference and explore how you can shape your future with us at capco.com . Capco’s AI Lab The AI Lab is a cross-disciplinary research and engineering centre that translates advanced AI research into robust, deployable solutions for clients and internal products. It runs applied research (ML and agentic/LLM systems, planning, simulation and evaluation), rapid prototyping and production engineering (APIs, CI/CD, observability, data platforms and cost/latency optimisation), and rigorous evaluation and safety work (benchmarks, red-teaming, monitoring, governance and compliance). The lab also supports client engagements and internal innovation by building demonstrators and reference architectures, transferring technology to delivery teams, publishing technical learnings, and maintaining the shared infrastructure, tooling and best practices that enable reproducible, secure and scalable AI deployment. Responsibilities Design and implement scalable, production-grade Python services that leverage LLMs and Agentic architectures. Design and implement robust agent workflows and orchestration patterns to automate complex business processes in regulated enterprise environments. Build and maintain reliable AI-enabled backend systems , including orchestration layers, tool integrations, knowledge a
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Drata is building the trust layer between great companies - automating compliance, managing risk, and helping organizations prove trust continuously as they scale. We're Dratanauts: a global crew of 600+ professionals united by a culture that rewards integrity, ownership, and raising the bar, no matter where in the world we're working from. Why Join the Drata Team? At Drata, you're not maintaining legacy compliance software - you're building the agentic AI platform defining what trust looks like for the next generation of companies. Here's what makes the work itself worth showing up for: Problems without a playbook: You'll work at the edge of AI and security, building agentic governance, continuous compliance, and real-time trust verification to solve problems that don't have an established answer yet. You're writing it as you go. Real ownership, not just process: Our values center on owning outcomes and raising the bar, not checking boxes. You're expected to have opinions and back them. A seat at the table: Your perspective is unique and valued. Open debate and diverse viewpoints are built into how decisions actually get made here, at every level. Growth at rocketship speed: Drata is scaling fast, which means scope grows fast too. High performers get more ownership, visibility, and experience. A crew, not just coworkers: Dratanauts consistently describe a "come as you are" culture with sharp, curious people—the kind of team that makes hard problems genuinely fun to solve. See what they say here and follow us on LinkedIn for company news, employee stories, and career updates. Job Summary: Drata is seeking a Senior Applied AI Engineer to drive the quality and effectiveness of our AI systems through rigorous experimentation, evaluation, and applied research. This is a research-focused role emphasizing experimentation and rigor over production engineering. You'll own the science behind how Drata's AI products retrieve, reason, and respond — and you'll work closely with
We're Hiring Senior AI Engineer (Generative AI Azure) Remote Immediate Joiners Preferred Salary: Up to 12 LPA We are seeking an experienced Senior AI Engineer to design, develop, and deploy enterprise-grade Generative AI solutions on Microsoft Azure. The ideal candidate will have strong expertise in Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), Azure AI Services, and modern AI engineering practices. Technical Summary • AI & LLMs: Azure OpenAI, GPT-4.x, OpenAI, Prompt Engineering, Prompt Chaining, Function Calling, Structured Outputs, Tool Calling, JSON Schema, Model Evaluation, Guardrails, Fine-tuning Concepts • Agentic AI: Multi-step Reasoning, Planning, Memory Management, Tool Orchestration, Multi-Agent Systems, Human-in-the-Loop Workflows, Reflection, Context Management, AI Observability • Frameworks: Semantic Kernel, LangChain, LangGraph, AutoGen, Azure AI Agent Service • RAG & MCP: Retrieval-Augmented Generation, Vector Search, Semantic Search, Hybrid Search, Embeddings, Knowledge Grounding, Citation Generation, Document Ingestion, Chunking, MCP Architecture, MCP Servers & Clients • Azure Technologies: Azure AI Foundry, Azure AI Search, Azure AI Document Intelligence, Azure Machine Learning, Azure Functions, API Management, Logic Apps, App Service, Container Apps, AKS, Azure Storage, Data Lake Gen2, Azure Key Vault, Azure Entra ID, Azure Monitor, Application Insights, Event Grid, Service Bus • Programming & DevOps: Python, C#, REST APIs, FastAPI, ASP.NET Core, JSON, YAML, Git, Azure DevOps, Docker, Kubernetes • Data Platforms: SQL Server, Azure SQL, PostgreSQL, Cosmos DB, Snowflake, Microsoft Fabric, Azure Databricks, Delta Lake, Vector Databases (Azure AI Search, Pinecone, Weaviate, Milvus, Qdrant) • Security & Governance: Responsible AI, Prompt Injection Prevention, RBAC, Content Filtering, Data Privacy, GDPR, ISO 27001, Azure Key Vault, Audit Logging & Monitoring • Nice to Have: Microsoft Copilo
Join a pioneering team at the forefront of financial technology innovation. We are building a cutting-edge, agentic AI platform designed to revolutionize the end-to-end credit risk model development lifecycle. By leveraging the power of Large Language Models (LLMs) and intelligent workflows, we aim to augment our quantitative modelers, dramatically increasing their productivity, enhancing model governance, and accelerating the delivery of critical risk models. We are seeking a senior, hands-on technology leader to drive this transformation. In this role, you will partner directly with quantitative analysts and key stakeholders to shape the most impactful use cases and then lead a team of talented developers to design, build, and deploy the generative AI platform that brings this vision to life. Key Responsibilities Strategic Vision & Stakeholder Partnership: Collaborate closely with quantitative model developers, Model Risk Management (MRM), and business leaders to deeply understand their pain points and translate them into a technical vision and product roadmap. Identify, scope, and prioritize use cases for the agentic workflow platform, ensuring they deliver measurable value and align with strategic objectives. Serve as the primary technical liaison between the engineering team and its users, ensuring a tight feedback loop and continuous alignment. Platform Design & Hands-On Development: Lead the architectural design of a scalable, robust, and secure agentic AI platform, including core components for orchestration, knowledge retrieval (e.g. RAG), and tool integration. Engage in hands-on software development to build foundational components, create proofs-of-concept, and tackle the most complex technical challenges. Design and implement secure integrations with internal data sources, external APIs, and various LLMs, ensuring compliance
Here’s a summary of the role: You are a seasoned AI engineer ready to design, ship, and own production‑grade agentic systems that solve real enterprise problems. At Diligent, you’ll take technical ownership of Compliance in a Box (CiaB) — a flagship AI platform reshaping how organisations manage governance, risk, and compliance at scale. You’ll architect and evolve the AI reasoning layer and agent orchestration framework at the heart of the product, shaping how multiple intelligent agents collaborate, reason, and operate safely in high‑stakes, regulated environments. This is hands‑on, deeply technical work — from system design to prompt strategy to evaluation — not research theatre. Partnering closely with product, security, and platform teams, you’ll make high‑impact decisions, move quickly, and see your work land in production fast. If you’re motivated by ownership, technical depth, and building AI systems that actually matter , this is your chance to set the standard for enterprise‑ready agentic AI. 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 understandin
AI Fullstack Engineer Poland ABOUT US Capco is seeking experienced and motivated AI Engineers to help design, build, and deploy AI-enabled solutions for clients in the financial services industry. As part of this engagement, you will work on complex business, technology, and data challenges, applying modern AI engineering practices to create scalable, reliable, and production-ready solutions. We are seeking professionals combines strong software engineering skills with practical experience in large language models, machine learning, data platforms, and modern AI application development. You will collaborate with client stakeholders, product teams, data specialists, and engineers to turn business needs into AI capabilities that are explainable, maintainable, and aligned with enterprise standards. SCOPE OF SERVICES AI Solution Delivery Design, develop, test, and deploy AI-enabled applications and services. Build solutions using large language models, machine learning, retrieval-augmented generation, semantic search, and agentic AI patterns where appropriate. Translate client business problems into technical designs, implementation plans, and working software. Develop reusable AI components, APIs, prompts, workflows, and evaluation approaches. Ensure AI solutions are scalable, reliable, secure, and suitable for production use. Data, Knowledge, and Retrieval Engineering Work with structured and unstructured data sources to support AI-enabled discovery, reasoning, and decision support. Build or integrate search, retrieval, ranking, and knowledge management capabilities. Develop approaches that help AI systems understand business context, data assets, metadata, documentation, and other enterprise knowledge sources. Improve the quality, relevance, traceability, and explainability of AI-generated outputs. Collaborate with data engineering and platform teams to ensure AI solutions are well integrated with existing data ecosystems. Technical
Drata is building the trust layer between great companies - automating compliance, managing risk, and helping organizations prove trust continuously as they scale. We're Dratanauts: a global crew of 600+ professionals united by a culture that rewards integrity, ownership, and raising the bar, no matter where in the world we're working from. Why Join the Drata Team? At Drata, you're not maintaining legacy compliance software - you're building the agentic AI platform defining what trust looks like for the next generation of companies. Here's what makes the work itself worth showing up for: Problems without a playbook: You'll work at the edge of AI and security, building agentic governance, continuous compliance, and real-time trust verification to solve problems that don't have an established answer yet. You're writing it as you go. Real ownership, not just process: Our values center on owning outcomes and raising the bar, not checking boxes. You're expected to have opinions and back them. A seat at the table: Your perspective is unique and valued. Open debate and diverse viewpoints are built into how decisions actually get made here, at every level. Growth at rocketship speed: Drata is scaling fast, which means scope grows fast too. High performers get more ownership, visibility, and experience. A crew, not just coworkers: Dratanauts consistently describe a "come as you are" culture with sharp, curious people—the kind of team that makes hard problems genuinely fun to solve. See what they say here and follow us on LinkedIn for company news, employee stories, and career updates. Job Summary: Drata's AI Platform team builds the production infrastructure that powers AI features across our compliance platform — from MCP servers that make Drata's data available to AI agents, to LLM workflow orchestration that automates SOC 2, TPRM, and policy analysis. You'll own the systems that sit between our AI models and our customers: tool definitions that agents actually understand,
Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Senior AI Engineer, Big Data & AI Solutions Overview The Security Solutions Data Science team develops AI and machine learning capabilities that help protect the global payments ecosystem from fraud and cyber threats. Supporting Mastercard’s Safety Net product, the team develops and enhances models that analyze billions of transactions and identify suspicious activity. As a Senior AI Engineer, you will work at the intersection of big data engineering and AI/ML, helping build and support the data, features, models, and production processes behind fraud detection. Ideal Candidate Profile You are a big data and AI/ML engineer who has used Apache Spark in a professional environment and has hands-on experience working within CI/CD-driven engineering environments. You understand how large-scale data moves from raw inputs through data and feature pipelines into machine learning models, and how those models are deployed, monitored, and improved in production. Large-scale data → Spark/PySpark → Data & Feature Pipelines → ML models → Production Deployment→ CI/CD→Monitoring & Drift Detection → Optimization & Retraining Experience with Generative AI, RAG, LLMs, or agentic AI is valuable, but the foundation for this role is large-scale data engineering and production AI/M
Senior Software Engineer, Applied AI About Syllo Syllo is on a mission to transform litigation. Our product is a unified litigation platform that enables lawyers and paralegals to safely harness the power of language models and agentic AI throughout the litigation life cycle. Since going to market, we have gained a diverse group of enterprise customers, including some of the biggest law firms and corporations in the country, and we are quickly expanding. By reducing the expense of litigation industry-wide, we aim to improve access to high-quality representation and promote the alignment of legal outcomes with merit. About the Role We are seeking a skilled and fast-moving Applied AI Engineer to join our team. This role is focused on the practical application of AI, specifically leveraging Large Language Models (LLMs), to build robust, scalable, and impactful user-facing features. This is an engineering-centric role. You will be an expert at building and integrating production systems, not primarily a research scientist. Responsibilities Design and build high-performance, production-level AI-powered features and services, with a focus on reliability and scalability. Develop robust engineering solutions to mitigate the inherent unreliability of LLMs. This includes implementing effective guardrails, validation pipelines, error handling, caching, and failover/fallback mechanisms to ensure a high-quality user experience even when the model misbehaves. Design long-running batch processing that is idempotent, resumable, and resilient to individual item failures. Focus on optimizing latency, throughput, and cost efficiency for all AI-powered services. Serve as an engineering expert in integrating models and data feeds with existing business logic and APIs. Define and implement evaluation for AI feature output quality, not only system correctness. Implement rigorous testing strategies, including unit, integration, and performance testing, to ensure the robus
Drata is building the trust layer between great companies - automating compliance, managing risk, and helping organizations prove trust continuously as they scale. We're Dratanauts: a global crew of 600+ professionals united by a culture that rewards integrity, ownership, and raising the bar, no matter where in the world we're working from. Why Join the Drata Team? At Drata, you're not maintaining legacy compliance software - you're building the agentic AI platform defining what trust looks like for the next generation of companies. Here's what makes the work itself worth showing up for: Problems without a playbook: You'll work at the edge of AI and security, building agentic governance, continuous compliance, and real-time trust verification to solve problems that don't have an established answer yet. You're writing it as you go. Real ownership, not just process: Our values center on owning outcomes and raising the bar, not checking boxes. You're expected to have opinions and back them. A seat at the table: Your perspective is unique and valued. Open debate and diverse viewpoints are built into how decisions actually get made here, at every level. Growth at rocketship speed: Drata is scaling fast, which means scope grows fast too. High performers get more ownership, visibility, and experience. A crew, not just coworkers: Dratanauts consistently describe a "come as you are" culture with sharp, curious people—the kind of team that makes hard problems genuinely fun to solve. See what they say here and follow us on LinkedIn for company news, employee stories, and career updates. Job Summary: Drata is advancing the frontier of compliance automation by integrating intelligent AI capabilities into its platform. We are seeking a Senior AI Engineer to help design, build, and scale robust, high-impact AI systems that improve operational efficiency, enhance decision-making, and support trust-critical enterprise workflows. This role focuses on solving complex, real-world probl
About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! About the Role - Multiple Levels This is an engineering delivery role where you’ll translate ambiguous customer needs into production-grade data, evaluation, and ML-assisted workflows. This is a high-impact role focused on end-to-end ownership of the AI data pipeline lifecycle, including developing and deploying ML-based workflows and building the technical foundations that make our human-in-the-loop (HITL) data generation and review faster, more reliable, and more effective. You’ll work at the critical intersection of data science, data engineering, AI engineering and operations, partnering closely with our DaaS Delivery Operations team and cross-functional stakeholders. You’ll develop technical specifications, design evaluation workflows, implement quality standards, measurement frameworks, and ML-assisted applications which improve our data pipelines and unblock projects through technical innovation. This role is ideal for someone who is comfortable working throughout the delivery lifecycle, rolling up their sleeves to solve complex multi-faceted problems, thrives as a technical communicator and works well as a key member of a team. Main Responsibilities Project Execution & Delivery Build and deploy evaluators, design and implement quality measurement systems to validate project outputs and ensure deliverables meet client expectations Generate synthetic datasets by developing or adapting existing pipelines to accelerate client engagements and aug
Who We Are Verkada is transforming how organizations protect their people and places with an integrated, privacy-sensitive AI-powered platform that includes solutions for video security, access control, air quality sensors, alarms, intercoms, and visitor management. We’ve got serious momentum in the market: more than 30,000 customers (including 100+ of the Fortune 500), a $5.8B valuation , more than $1 billion in annualized bookings, and backing from CapitalG, Sequoia Capital, General Catalyst, Felicis Ventures, Next47 and more. Physical AI is one of the most consequential technology shifts of our time, and Verkada is at the center of it. You can look at all kinds of communities to see our platform’s impact in the world. It's the retailer that uses our agentic AI to deter theft before it happens. The warehouse that uses AI-powered alerts to make sure its team is protected on the floor with proper PPE. The school that’s alerted to a threat in real-time and triggers a lockdown in seconds, not minutes. We’re rapidly scaling this impact: today, more than 2 million Verkada devices are deployed across 170+ countries. What You'll Do Own the end-to-end development of on-device camera platform features in C++ and Golang . Collaborate with the product team to turn requirements into scalable, production-ready solutions aligned with product vision and customer needs. Partner with streaming, storage, and AI engineering teams to deliver features optimized for edge computing environments . Lead code reviews, guide debugging efforts, and uphold coding standards to ensure a high-quality, maintainable codebase . Drive and coordinate regular over-the-air (OTA) releases, balancing speed of delivery with stability and reliability. What You Bring BS/MS in Computer Science, Electrical Engineering, or related field. 5+ years of professional experience in systems software development for performance- and resource-constrained environments. Proficient in at least one systems progr
Who We Are Verkada is transforming how organizations protect their people and places with an integrated, privacy-sensitive AI-powered platform that includes solutions for video security, access control, air quality sensors, alarms, intercoms, and visitor management. We’ve got serious momentum in the market: more than 30,000 customers (including 100+ of the Fortune 500), a $5.8B valuation , more than $1 billion in annualized bookings, and backing from CapitalG, Sequoia Capital, General Catalyst, Felicis Ventures, Next47 and more. Physical AI is one of the most consequential technology shifts of our time, and Verkada is at the center of it. You can look at all kinds of communities to see our platform’s impact in the world. It's the retailer that uses our agentic AI to deter theft before it happens. The warehouse that uses AI-powered alerts to make sure its team is protected on the floor with proper PPE. The school that’s alerted to a threat in real-time and triggers a lockdown in seconds, not minutes. We’re rapidly scaling this impact: today, more than 2 million Verkada devices are deployed across 170+ countries. What You'll Do Own the end-to-end development of on-device camera platform features in C++ and Golang . Collaborate with the product team to turn requirements into scalable, production-ready solutions aligned with product vision and customer needs. Partner with streaming, storage, and AI engineering teams to deliver features optimized for edge computing environments . Lead code reviews, guide debugging efforts, and uphold coding standards to ensure a high-quality, maintainable codebase . Drive and coordinate regular over-the-air (OTA) releases, balancing speed of delivery with stability and reliability. What You Bring BS/MS in Computer Science, Electrical Engineering, or related field. 5+ years of professional experience in systems software development for performance- and resource-constrained environments. Proficient in at least one systems progr
Position Overview: We are looking for a Senior Software Engineer to drive technical excellence, architect complex systems, and elevate our engineering team. You will own critical technical decisions, lead major initiatives from conception to delivery, and set the standard for engineering quality across our products. As a senior engineer, you will architect and lead the development of sophisticated AI-enabled features and infrastructure. This includes designing MCP server architectures, building advanced RAG systems, implementing agentic AI workflows, and establishing patterns that scale across our product portfolio. You will combine deep technical expertise in both traditional software engineering and AI/ML to deliver production-grade solutions. What You'll Do Lead the design and implementation of AI integration infrastructure (MCP servers, orchestration layers, API gateways) Build sophisticated AI features including advanced RAG systems, agentic workflows, and multi-step reasoning Establish AI engineering best practices, security patterns, and quality standards Lead technical initiatives from requirements through production deployment Make critical architectural decisions balancing performance, scalability, cost, and maintainability Design AI evaluation frameworks and implement quality benchmarks Debug and resolve complex production issues across traditional and AI systems Required Qualifications Tech Stack Core: Node.js, React, TypeScript, AWS, PostgreSQL, MSSQL, Docker AI & Integration: Python, MCP, AWS Bedrock, LangGraph/Semantic Kernel, Vector Databases, RAG Core Technical Skills 5+ years professional development with proven track record of delivering complex systems Strong Node.js and JavaScript/TypeScript expertise Advanced React and frontend architecture skills Extensive AWS architecture experience Expert PostgreSQL database design, optimization, and performance tuning Deep understanding of microservices, distributed systems, and
We are investing in agentic AI and need a Senior AI Engineer to lead the design and delivery of these systems. This is a foundational hire: you will own both the agent-facing workstreams — pipelines, orchestration, conversational interfaces — and the underlying context layer that makes them reliable, including memory management, knowledge graph integration, and retrieval infrastructure. You will work closely with data engineers, project leads, and client stakeholders, and play a key role in shaping how Lynx builds and ships AI solutions at scale. What This Involves: Lead the architecture and delivery of agentic AI systems end-to-end: agents, orchestration, tool use, and multi-step reasoning workflows. Own the context layer: design and implement memory architectures (episodic, semantic, working memory) and integrate GraphRAG and knowledge graph retrieval into agentic pipelines. Build robust RAG systems — including vector retrieval, graph traversal, and hybrid search — and ensure retrieval quality through evaluation frameworks. Translate client requirements into technical designs, presenting approaches and trade-offs to both technical and non-technical stakeholders. Define standards and reusable patterns for agentic AI development that other engineers at Lynx can build on. Set up observability, evaluation, and monitoring pipelines to ensure AI systems perform correctly in production. Requirements: 5–8 years of software or ML engineering experience, with at least 2–3 years building LLM-based or agentic AI systems in production. Deep hands-on experience with agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, or similar) and LLM APIs (OpenAI, Anthropic, etc.). Strong understanding of agent design patterns: ReAct, planning loops, tool use, multi-agent coordination, and memory architectures. Practical experience with GraphRAG or knowledge graph-based retrieval (e.g., Neo4j, Microsoft GraphRAG) and vector databases (Pinecone, Weaviate, Qdrant, etc.). Proficiency in
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