Top AI Engineer Jobs

Own and evolve Syndio’s AI platform runtime, including agent orchestration, tool calling, memory, context management, RAG, evaluations, observability, and production reliability. Design and ship backend systems in Python on GCP and Kubernetes, establish platform contribution standards, support compliance requirements, collaborate with product teams, and participate in incident response and on-call operations.

Leads a technical AI/ML engineering team while remaining hands-on in designing, developing, testing, and deploying software prototypes. Owns architecture, technical direction, planning, execution, risk management, customer communication, and delivery across R&D and funded projects. Conducts design and code reviews, mentors engineers, supports proposals, and translates mission needs into practical solutions for national security applications including air, space, and missile defense.

Own cloud infrastructure, CI/CD pipelines, observability, incident response, recovery procedures, and reliability automation across applications and AI agents. The role uses Infrastructure as Code, scripting, monitoring, SLOs, and AI-assisted operations to improve platform resilience and reduce toil.

Build and deploy AI-powered products across the frontend, backend, APIs, databases, and model integrations. Own features end to end, design maintainable interfaces and data models, connect applications to LLMs and agents, use AI-assisted coding tools, write tests, review code, troubleshoot production systems, and mentor teammates.

Lead HPC and AI benchmarking across CPU, GPU, networking, memory, and storage platforms. Analyze scientific, engineering, LLM, training, inference, and I/O workloads; identify bottlenecks; and optimize applications, frameworks, libraries, compilers, runtimes, and system software. Apply parallel computing, GPU acceleration, profiling, and memory and I/O optimization while translating findings into customer-focused recommendations.

Design, implement, and support modern endpoint management across Microsoft and Apple environments. Manage Intune policies, security baselines, applications, provisioning, migrations, and Apple enrollment workflows. Develop PowerShell automation, version-controlled configurations, and CI/CD-aligned processes to improve operational consistency. Troubleshoot endpoint issues, document procedures, support escalations, provide technical guidance, and apply AI tools to improve service delivery and automation.

Hands-on senior quality engineer building automation-first test frameworks across API, UI, integration, data, and end-to-end workflows. Use AI/GenAI tools to accelerate test design, triage, and coverage. Improve unit test strategy, CI/CD quality gates, observability, and resilience. Analyze defect patterns, create quality dashboards, and partner with engineering and product to increase automation coverage and reduce escaped defects in regulated wealth management systems.

Leads software engineering initiatives within an agile banking technology team. Designs, develops, reviews, debugs, and troubleshoots secure production code; drives responsible AI-assisted development practices; improves automation and operational stability; evaluates architectures and vendors; and promotes modern engineering technologies. The role requires advanced programming, generative AI and machine learning familiarity, distributed systems, cloud platforms, microservices, APIs, databases, containerization, performance testing, and chaos engineering experience.

Develops AI-driven Celonis prototypes and proof-of-concept solutions using SQL, PQL, machine learning, and LLMs. Consults with customers to identify business challenges, presents value propositions, quantifies ROI, leads platform demonstrations, and builds trusted advisor relationships. Partners with sales, implementation, product, and engineering teams to deliver value realization and reusable best practices through the 12-month Orbit Program.

Develop and deploy machine learning algorithms for defense and commercial applications, working with images, text, graph data, NLP, computer vision, reinforcement learning, and large language models. Responsibilities include analyzing large datasets, building inference models, using cloud services for training and deployment, researching emerging methods, and preparing technical documentation. The role requires Python, machine learning experience, a relevant bachelor’s degree, at least two years of experience, and an active TS/SCI clearance with CI Poly.

Lead researchers and developers in creating computer vision AI/ML solutions for remote sensing, including automatic target recognition and multimodal EO/SAR data fusion. Analyze datasets, research supervised and unsupervised approaches, train and optimize deep learning models, deploy them to cloud environments, communicate technical findings, and produce documentation. The role requires technical leadership, customer collaboration, and an active TS/SCI clearance.

Develop and implement machine learning algorithms across computer vision, natural language processing, time-series, graph data, reinforcement learning, and large language models. Analyze large multi-domain datasets, apply current research, document solutions, and support AWS-based training and deployment pipelines. Mentor team members and collaborate within interdisciplinary teams. The role requires substantial AI/ML development experience, strong Python and ML library skills, and an active TS/SCI clearance.

Develop and implement AI/ML algorithms across computer vision, NLP, time series, reinforcement learning, and large language models. Analyze multimodal datasets, apply research findings, document systems, support AWS-based training and deployment pipelines, and mentor team members. The role requires substantial AI/ML development experience, advanced Python and machine learning library proficiency, deep learning expertise, and an active TS/SCI clearance.

Develop and implement AI/ML algorithms for defense and commercial applications, analyzing image, text, and graph datasets to build actionable models. Use cloud services to train and deploy models, apply statistical and machine learning techniques, review research, and create technical documentation. The role involves collaboration with software developers and researchers and requires an active TS/SCI clearance with CI Poly.

Leads researchers and developers in building computer vision AI/ML solutions for remote sensing, including automatic target recognition and multimodal EO/SAR data fusion. Responsibilities include preparing datasets, researching supervised and unsupervised methods, training and optimizing deep learning models, deploying algorithms to cloud environments, communicating technical findings, and documenting systems. The role requires active TS/SCI clearance and provides technical leadership from prototype through operational deployment.

Build complete applications, workflow automations, and basic AI agents using AI coding agents. Translate customer needs into specifications, deploy solutions, instrument usage and outcomes, evaluate AI-generated output for security and quality, engage with customers, and document effective prompts and development patterns.

Build complete applications, workflow automations, and basic AI agents by directing AI coding agents. Translate customer needs into specifications, deploy full-stack solutions, instrument usage and outcomes, evaluate AI-generated work for security and reliability, engage with customers, and document effective prompts and development patterns.

Join Celonis’s 12-month Orbit Program as an Associate Value Engineer. Consult customers, identify business challenges, build AI and machine-learning prototypes, develop SQL and PQL data models, lead proof-of-concept projects, present solutions to executives, quantify ROI, and establish trusted customer relationships. The role combines technical analytics, enterprise software consulting, customer engagement, and value realization, with mentorship and training provided.

Own product development for Elixir-based applications, translating client needs into specifications and delivery plans. Design architecture, APIs, data models, integrations, scalability, security, and maintainability. Direct AI coding-agent workflows, review generated work, write code when needed, and ensure testing, CI, QA, and controlled releases. Communicate proactively with clients, troubleshoot complex issues, and improve agent harnesses, engineering standards, observability, and quality gates.

Set technical direction for Root’s AI platform, including infrastructure, tooling, shared services, governance, reliability, security, observability, and cost management. Lead cross-team initiatives, guide AI and LLM architecture decisions, establish operating standards, shape technical roadmaps, resolve complex tradeoffs, and mentor engineers and technical leaders across the organization.

Owns the architecture, engineering, operation, and roadmap of a secure AI research platform. Builds scalable CPU/GPU cloud infrastructure, self-service research environments, platform automation, CI/CD, orchestration, and infrastructure-as-code. Partners with AI researchers to enable LLM, agentic AI, retrieval, inference, and benchmarking workloads, while maintaining reliability, observability, security, cost controls, incident response, and operational readiness in a regulated enterprise.

Lead the architecture and evolution of enterprise developer telemetry and real-time data platforms. Build scalable streaming pipelines, AI inference capabilities, data lake solutions, observability frameworks, and privacy controls. Correlate AI engineering metrics with business outcomes while mentoring engineers, shaping technical strategy, evaluating build-versus-buy decisions, and contributing directly through prototypes, code patterns, and reusable data products.

Designs, builds, and operationalizes secure AI-powered data experiences, including natural-language analytics agents and agentic workflows. Owns AI tooling, retrieval, prompting, evaluation, Azure runtime architecture, deployment, monitoring, and supportability. Partners with data engineering, cybersecurity, IT, and business stakeholders to ensure governed, explainable, privacy-preserving solutions. Develops reusable AI components, responsible-AI guardrails, enablement materials, and adoption strategies for enterprise users.

Build AI-driven systems for blockchain security, including smart contract analysis, vulnerability discovery, exploit analysis, threat detection, and security investigations. Develop AI agents that reason over codebases, protocol interactions, transactions, and wallet activity. Collaborate with security researchers and infrastructure teams on monitoring and incident response while researching blockchain attack techniques, Web3 infrastructure, and AI security trends.

Design, deploy, and scale production AI/ML solutions for healthcare, including predictive models, generative AI, statistical analysis, microservices, APIs, and MLOps pipelines. Analyze complex clinical datasets, implement model monitoring and governance, evaluate emerging AI technologies, and collaborate with engineering, data, product, and clinical teams to improve care delivery and operational efficiency.