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Discover how advanced AI technology can improve the lives of the often-overlooked heroes of healthcare – the caregivers. Our AI platform revolutionizes daily work in caregiving by automating time-consuming tasks such as documentation and/or scheduling. This allows caregivers to focus more on the care itself. Our goal is to significantly reduce the workload and sustainably improve the quality of care. If you want to work on complex backend systems with real-world impact, move fast, use AI tools every day, and take real ownership, we would like to hear from you.
Role Description We are looking for a high-agency AI Engineer to help us build new AI features faster and improve the quality, reliability, and speed of existing AI workflows. This is a hands-on engineering role. Not research. Not prompt-only. You will turn ambiguous product ideas into working, production-ready AI features. The role is mostly focused on shipping AI product features, with some AI systems and infrastructure work where needed. You will work closely with product and engineering, but we expect you to take real ownership. You should be comfortable moving fast, making technical decisions under ambiguity, and using AI development tools such as Claude Code, Codex, Cursor, Copilot, or similar every day. As our Applied AI Engineer, you will: - Build new AI-powered product features from idea to production - Improve existing AI workflows for quality, reliability, latency, and user value - Design and implement LLM-based workflows, structured outputs, validation logic, and fallback behavior - Build evaluation loops, tests, and quality checks for AI-generated outputs - Integrate AI capabilities into existing product and backend systems - Work with commercial and open-source LLMs without being tied to one specific provider - Support self-hosted model workflows where they make sense for quality, speed, cost, or control - Debug AI feature failures across inputs, outputs, data, backend logic, and user flows - Use AI development tools as a core part of your daily workflow - Ship quickly while keeping production quality high Qualifications - Strong software engineering skills, especially in Python or a comparable backend language - Experience building AI-powered product features or LLM-based workflows - Ability to turn ambiguous product ideas into working software quickly - Strong understanding of how to design, test, validate, and improve AI outputs - Experience integrating AI workflows into production systems - Strong debugging instincts across application logic, data, model outputs, and user-facing behavior - Experience with evaluation, testing, validation, or quality checks for AI-generated outputs - Serious experience using AI development tools such as Claude Code, Codex, Cursor, Copilot, or similar as part of your daily workflow - High intelligence, fast learning speed, bias to action, and ownership mindset - Comfortable with ambiguity, fast decisions, and a high-trust startup environment - Clear written and spoken English Requirements - Experience with frontend or fullstack product development - Experience with self-hosted LLMs, model serving, inference optimization, or similar systems - Experience with open-source LLMs and related deployment workflows - Experience improving latency, cost, quality, or reliability of AI systems - Experience with healthcare software, healthcare data, or regulated environments - Experience working with structured data extraction, documentation automation, voice workflows, or workflow automation - German language skills - Knowledge of nursing homes or elderly care workflows Benefits - Remote work - Fair compensation based on skills, experience, and location - Ownership of important backend systems - Work on software used in real healthcare workflows - Modern AI-native development workflow - Room to grow with the company
SS8 is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity or expression, sexual orientation, age, disability, protected veteran status, or any other status protected by applicable law. SS8 does not accept unsolicited resumes from staffing agencies, search firms, or third parties. Any resumes submitted without a signed agreement in place will be considered the property of Company, and no fees will be paid if a candidate is hired as a result.
Role Description We’re looking for a highly motivated and visionary Full-Stack Engineer with deep expertise in Artificial Intelligence to join our core engineering team. In this role, you will be instrumental in advancing our flagship platforms like Intellego® XT, Discovery, and LocationWise. You will design, build, and deploy complex end-to-end distributed systems and AI-powered applications that process massive volumes of multi-modal investigative data. Working at the intersection of full-stack engineering and AI, you will build next-generation web interfaces, geospatial intelligence tools, and generative AI pipelines that help law enforcement turn complex data into actionable clarity. What You'll Work On - Developing complex, end-to-end distributed web applications on cloud-native platforms, primarily utilizing AWS. - Integrating and deploying LLM and deep learning-based applications, including voice analytics (such as OpenAI Whisper), document analysis, and image/video intelligence (e.g., artifact detection) using open-source models. - Building interactive, LLM-driven frontends and complex UI applications involving dynamic dashboards and precise mapping/geolocation for our location intelligence products. - Designing scalable, high-throughput backend architectures utilizing Kubernetes, Kafka, Redis and distributed data stores. - Utilizing AI-assisted coding tools (like Claude Code, Codex, or Devin) to dramatically accelerate development, code reviews, and automated testing cycles. - Collaborating with cross-functional teams to engineer data platforms that fuse network intelligence, open-source intelligence, and high-precision location data into a "single pane of glass." Key Responsibilities - Architect, implement, and maintain high-performance full-stack applications using React (and related ecosystems) for the frontend and robust distributed technologies for the backend. - Design, implement and troubleshoot microservices within Kubernetes-based environments, ensuring high availability and fault tolerance. - Develop and optimize scalable data processing pipelines utilizing distributed systems theory, caching (Redis), search engines (OpenSearch), event streaming (Kafka), and diverse database architectures (Graph, Relational, Document, Multimodal). - Drive the operationalization of Deep Learning and Generative AI models into production environments to augment human analysts. - Implement secure, hardened access controls via robust OAuth and Active Directory (AD) integrations to maintain evidentiary integrity and auditability. - Lead by example in modern software engineering practices, leveraging AI coding assistants for enhanced productivity and mentoring peers. Required Experience & Qualifications - 5+ years of professional full-stack development experience building complex, large-scale distributed systems. Familiarity with Java, Python and JavaScript/Typescript based development. - Extensive hands-on experience with cloud-native platforms such as AWS (preferred), GCP, or Azure. - Proficiency in Kubernetes-based orchestration, deployment, and operational troubleshooting. - Solid engineering background in distributed systems and state management (Kafka, Redis, OpenSearch, and various multi-modal databases). - Deep expertise in frontend development using React.js, with a proven track record of delivering complex UIs (e.g., data-heavy dashboards, mapping, and geo-location products). Must Have - Verifiable experience building and deploying Deep Learning and Generative AI solutions (e.g., LLM-based UIs, voice/image/video analytics using open-source models). - Practical experience incorporating AI-assisted coding tools (Claude Code, GitHub Copilot/Codex, Devin) into your daily engineering workflow. - Strong understanding of enterprise security concepts, specifically OAuth and AD integration. Nice to Have - Hands-on DevOps, CI/CD, and infrastructure-as-code deployment experience, specifically within AWS. - Additional background in large-scale big data platform development, data crawling and data engineering/processing. - Previous experience in lawful intercept, telecommunications data (5G, IMSI/IMEI tracking), cybersecurity analytics, or digital forensics. - Proficiency with Golang and Rust. Compensation & Benefits - The expected base salary range for this position is $110,000 - $135,000. Actual compensation will be determined based on the candidate’s skills, experience, and qualifications. - This role is also eligible to participate in SS8’s corporate bonus program, subject to the terms of the applicable plan. - We offer a comprehensive benefits package including medical, dental, vision, 401(k) with company match, and paid time off. Equal Opportunity Employer SS8 is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity or expression, sexual orientation, age, disability, protected veteran status, or any other status protected by applicable law. SS8 does not accept unsolicited resumes from staffing agencies, search firms, or third parties. Any resumes submitted without a signed agreement in place will be considered the property of Company, and no fees will be paid if a candidate is hired as a result.
Enabling the development of electric vehicles of the future. From #materialscience to ultimate #emobility products.
Role Description We’re looking for an AI Software Engineer to help build the next generation of UJET's AI products: Spiral and AXO. This is a high-impact role for someone who thrives in ambiguity, enjoys moving across the stack, and wants to turn cutting-edge model capabilities into real-world product experiences. - Work across backend systems, AI services, product features, APIs, and infrastructure. - Build agent workflows in Python, ship customer-facing features in TypeScript, improve evals and reliability, or design systems that process large-scale conversational data securely and efficiently. This role is ideal for an engineer who is deeply practical about AI: someone who uses AI-assisted development naturally, understands how to build with and around LLMs, and cares about reliability, performance, and user impact as much as model quality. We value curiosity highly. The best people in this role are excited to dig into messy problems, ask good questions, and iterate until the system is measurably better. Qualifications - 3-5 years of professional software engineering experience, with strong hands-on experience building production systems. - Strong experience as a generalist engineer who can move fluidly between backend systems, frontend, AI services, APIs, and product development. - Excellent programming skills in Python and TypeScript. - Experience shipping AI agents, LLM-powered applications, or other production AI systems, including prompt and tool orchestration, evaluation, and cost/reliability tradeoffs. - Strong product instincts and comfort working in ambiguous environments where the right solution is not obvious at the start. - Experience building and operating systems on AWS/GCP in production. - Comfort working with large, messy datasets and building pipelines that turn unstructured inputs into dependable product functionality. - Strong SQL and data systems fundamentals. - A bias toward ownership, speed, and pragmatic execution. - Experience building AI-native products from 0 to 1. - Familiarity with conversational data, support platforms, CRM/CCaaS integrations, or customer experience tooling. - Experience with observability, evaluation frameworks, and production reliability for AI systems. Requirements - Build and own product and platform capabilities across Spiral and AXO, from early prototypes to production systems. - Design and implement AI-powered workflows, agent capabilities, and backend services that are scalable, secure, and reliable. - Develop high-performance APIs, async workers, and application logic in Python and TypeScript. - Ship user-facing product features and internal tools that make advanced AI systems useful and intuitive for customers. - Architect and improve data ingestion, parsing, and analysis pipelines that transform raw customer interaction data into structured, actionable insights. - Partner across engineering, product, and design to translate ambiguous product ideas into robust technical systems. - Own infrastructure and deployment patterns on AWS/GCP, with a focus on reproducibility, observability, security, and cost efficiency. - Improve system quality through evaluation, monitoring, logging, alerting, and operational best practices. - Help define engineering standards, review code, and mentor teammates working on distributed systems and AI applications. Benefits - Medical, dental, vision, 401(k) plan, commuter benefits, and more.
Dynatrace is a global application performance management software firm and a former member of Compuware. As an employer, the company is in support of helping its team achieve a hea
We put AI firstWe're looking for a Principal Generative AI Engineer to build AI systems that connect development workflows with production observability. You'll design and ship agentic tooling that helps engineers understand code, assess the impact of changes before they hit production, and act on real runtime signals. Your role at DynatraceWe are looking for a visionary, technically excellent engineer who is ready to design and ship production-grade agentic AI systems that bridge the gap between code context and runtime signals. You should thrive on a foundation of freedom, feedback, and responsibility, bringing a startup-like drive backed by the reach of a global platform. - Design, build, and ship agentic AI systems and tooling that helps engineers understand code, assess the impact of changes before they hit production, and act on real runtime signals. - Build production LLM systems end to end, managing prompting, tool calling, retrieval, memory management, and the agent loops that tie them together. - Define the evaluation strategies, metrics, and datasets that make agent quality measurable, ensuring we ship on evidence and catch regressions across model and prompt changes. - Connect development workflows with production observability, turning code context and runtime signals into reliable, actionable insight, and collaborate with product, design, and platform teams to identify developer problems. - Set technical strategy and architectural direction for the team's AI systems, mentor engineers across the organization, and take full ownership of systems using Dynatrace to monitor and optimize them. What will help you succeedYou are a seasoned technical leader with a strong software engineering foundation and proven hands-on experience deploying complex LLM applications. You possess the engineering judgment to navigate ambiguous, fast-moving spaces and set clear architectural direction for your team. - Degree in Software Engineering or equivalent practical experience in software development, combined with a track record of technical leadership and the judgment to set direction in an ambiguous, fast-moving space. - Extensive experience shipping production systems that use LLMs, including prompting, tool calling, evaluation, and iteration. - A strong foundation in at least one of: developer tooling (IDEs, compilers, static analysis, code intelligence), AI/ML engineering, or large-scale distributed systems. - Hands-on experience with agentic patterns, specifically planning, tool use, retrieval, and memory management. - The ability to evaluate and critique AI-generated output, understanding why a model is wrong, not just that it is, with familiarity with observability and the Dynatrace platform as a strong advantage. Why you will love being a Dynatracer - Dynatrace is a leader in unified observability and security. - We provide a culture of excellence with competitive compensation packages designed to recognize and reward performance. - Our employees work with the largest cloud providers, including AWS, Microsoft, and Google Cloud, and other leading partners worldwide to create strategic alliances. - You'll get to work at the forefront of innovation with Dynatrace Intelligence—the industry's first agentic operations system. Bringing together deterministic and agentic AI, it helps teams understand what's happening, why it matters, and what to do next— automatically. - Over 50% of the Fortune 100 companies are current customers of Dynatrace. Compensation and RewardsThe base salary range for this role is $146K - $220K. When determining your salary, we consider your experience, skills, education, and work location. Our total compensation package includes unlimited personal time off, an employee stock purchase plan, and a reward system. We also offer medical/dental benefits and a company-matched 401(k) plan for retirement. Equal Employment OpportunityDynatrace provides equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other protected characteristic. We actively foster an inclusive workplace that celebrates differences and promotes accessibility, collaboration, and growth for all.
Using CaaS (Codeless-as-a-Service) to accelerate time-to-market & eliminate legacy code for the enterprise 🚀
• Report directly to our VP of Agentic AI • Shape the core intelligence and behavior of the agent — how it interprets intent, plans, assists, and recovers from failure — so that it reliably helps users build working Unqork applications. • Help scale the backend that powers the agent in production, contributing to a service that stays fast, observable, and resilient as usage grows. • Drive how we measure and raise agent quality over time, turning real-world usage into a feedback loop that makes the product steadily more capable and trustworthy.
• Help build next-generation AI-powered product experiences. • Build AI-driven product features that integrate LLMs (like GPT, Claude, or Gemini) via APIs. • Prototype quickly and iterate fast, turning rough concepts into working interfaces and tools. • Develop front-end experiences in React that make complex AI outputs intuitive and delightful. • Collaborate with backend engineers to design APIs and data pipelines that support AI interactions. • Work across the stack when needed — from front-end interfaces to backend service integration in Python. • Experiment with new LLM capabilities, libraries, and prompt engineering approaches. • Contribute to internal tools for data cleaning, model evaluation, and content generation workflows.
Global leader in engagement platform technologies and data-driven experiences that cultivate brand advocates worldwide.
• Own a product capability end to end, from architectural decisions through production outcomes, cutting through every layer: entry points, orchestration, intelligence, tools, data, and observability • Your work directly shapes how Augeo's clients engage tens of millions of users • Build and ship mission-critical AI agents that drive revenue growth across finance, healthcare, telecom, and commerce • Define how AI agents are built at Augeo • Drive the Agent Development Life Cycle (ADLC) from initial pilot through production iteration • Build the shared platform: agent orchestration, agentic workflows, ML models, and data infrastructure • Work across Augeo with engineers, product leads, and end users to understand needs, close feedback loops, and ensure the platform compounds with every interaction • Shape the team and participate in hiring
• Provide strategic leadership and direction to 2 to 3 small, senior-caliber engineering teams • Guide teams in understanding client needs, setting project goals, and ensuring successful implementation • Manage 2–3 high-performing implementation teams of senior engineers • Support the company’s rapid growth as we double our client base • Drive delivery against the product roadmap • Champion collaborations with TA and existing external sourcing vendors • Refine onboarding methodologies • Engage with organizational leaders to co-design and champion career progression frameworks • Mentor an Engineering Talent Manager • Dive deeper into analytics and connect the dots between talent metrics and broader business objectives • Champion an AI-first engineering culture • Facilitate the creation and management of data and information repositories • Foster an environment of proactive domain-specific knowledge sharing among team members • Pioneer refinements in delivery processes • Advocate for and pursue expertise in advanced talent management strategies • Maintain regular and reliable attendance
• Write and ship production AI code daily — you are an active contributor. • Architect agentic AI workflows using LangGraph, Temporal, Pydantic — stateful, multi-agent workflows built for enterprise scale and reliability. • Own AI observability via LangFuse: tracing, prompt versioning, evaluation, and performance benchmarking across all model interactions. • Set AI engineering standards for agent design patterns, RAG, prompt management, context optimization, and tool-calling strategies. • Partner with product and platform teams to deliver AI architectures that meet enterprise SLA, security, and compliance requirements. • Evaluate and adopt emerging tooling — benchmarking LLM providers, orchestration frameworks, and agentic stack improvements. • Mentor engineers as a natural extension of your work — sharing knowledge through code reviews, pairing sessions, and design discussions, not through management overhead. • Represent Acquia's AI capabilities in customer architectural reviews, technical discovery, and roadmap conversations.
We are a global leader in cell-free DNA (cfDNA) testing, dedicated to oncology, women’s health, and organ health.
• Design, build, and deploy agent-based AI systems that improve the quality and reliability of clinical data extraction in production. • Own technical design and delivery for agent workflows. • Integrate new AI capabilities into existing production platforms with attention to performance, scalability, and cost. • Partner with clinical AI, engineering, and product teams to prioritize problems, define success metrics, and ship incremental improvements. • Develop evaluation and monitoring approaches to measure impact, guide iteration, and support safe deployment in a regulated environment. • Provide technical leadership through clear documentation, design decisions, and pragmatic tradeoffs across accuracy, cost, and delivery timelines.
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Python, TypeScript, AWS, Cloud, Flask, Java
