Top Artificial Intelligence Jobs

Provides technical advisory and hands-on engineering support for government AI applications. Evaluates LLMs, retrieval-augmented generation, agentic workflows, orchestration frameworks, architectures, and AI evaluation methods. Develops prototypes, technical guidance, engineering recommendations, and stakeholder briefings while assessing reliability, observability, guardrails, integration, and operational risks. Collaborates with engineers, product leaders, mission users, and government leadership, requiring extensive AI/software experience and an active TS/SCI clearance with polygraph.

Use Gmail, Google Calendar, booking platforms, and AI assistants to complete realistic digital tasks. Provide clear instructions, verify AI-generated work, grade and annotate outputs, test edge cases, submit structured evaluation data, and collaborate with project contributors to improve guidelines and consistency. The role requires strong attention to detail, communication, organization, and independent remote work.

Designs, develops, tests, and optimizes generative and agentic AI solutions using LLMs, RAG, prompt engineering, NLP, and automation. The role creates AI interactions, workflows, safety filters, governance, observability, and explainability frameworks; partners with technical and business stakeholders; conducts testing; documents reusable solutions; and mentors junior staff. The position is fully remote and emphasizes secure, ethical, and compliant AI implementation.

Build and test AI-powered prototypes that address customer and operational challenges. Translate business needs into product requirements, user stories, metrics, and delivery plans. Collaborate with Product, Engineering, Data, Security, Operations, and business teams through UAT and launch. Evaluate solution performance, adoption, risk, scalability, and customer impact while ensuring secure, responsible, privacy-compliant implementation.

Provides architecture leadership for enterprise Data & Analytics initiatives. Defines end-to-end cloud and hybrid solution architectures, governs architecture reviews, modernizes data platforms, and designs secure, scalable solutions supporting analytics, reporting, AI/ML, and digital transformation. Partners with business and technical stakeholders to create roadmaps, implementation plans, architecture artifacts, and governance standards. Presents solutions to architecture review boards and guides data strategy, security, compliance, integration, and responsible AI practices.

Leads analytics-focused workstreams within enterprise transformation programs, driving cost reduction, productivity, revenue growth, and digital transformation initiatives. Structures ambiguous business problems, develops analytical models using Excel, Python, and Power BI, and translates insights into executive recommendations. Manages workplans, risks, dependencies, stakeholder alignment, and cross-functional execution across Operations, Technology, and Finance.

Senior individual contributor leading Sales BI strategy and AI transformation. Responsibilities include developing enterprise Power BI dashboards and data models, defining sales metrics, delivering production AI agents and automated analytical workflows, shaping Snowflake and AI analytics infrastructure, leading cross-functional initiatives, mentoring analysts, and influencing sales executives through data-driven recommendations. The role requires measurable adoption and business impact from AI-enabled analytics, without direct people-management responsibility.

Leads enterprise AI platform strategy across multiple teams, including LLMs, RAG, agentic workflows, connectors, evaluation, governance, and model risk. Serves as the highest-level technical authority for complex AI architecture and reliability challenges, advises executives, establishes engineering standards, mentors senior technical leaders, manages model and infrastructure vendor strategy, and guides safe AI adoption in a regulated healthcare environment.

Leads architecture and delivery of enterprise generative AI platforms and LLM-powered systems, including RAG, agentic workflows, model integrations, evaluation tooling, and governance. Owns platform architecture, security, privacy, observability, cost attribution, and responsible AI practices in a regulated healthcare environment. Mentors AI engineers, establishes technical standards, leads design reviews, evaluates vendors and models, and partners with engineering, product, legal, compliance, and privacy teams.

Researches AI tools, platforms, and vendors; evaluates privacy, security, transparency, contractual, regulatory, and reputational risks; gathers evidence and prepares submission packages for governance review. Maintains tracking records, validates policy alignment, coordinates responses across Legal, Security, Privacy, Procurement, and Technology teams, and improves research and submission processes. The role also monitors emerging AI governance developments and contributes to new policies and guidance.

Owns the end-to-end governance review and implementation of enterprise AI products. The role manages submissions through cross-functional Legal, Privacy, Security, Procurement, and technology reviews; coordinates blockers, schedules, documentation, and risk escalation; and leads approved solution onboarding across cloud, Okta, ServiceNow, CSDM, and enterprise technology teams. It also improves governance processes, develops implementation playbooks, and ensures compliant post-launch operations.

Leads enterprise-wide AI-enabled quality engineering transformation across the software development lifecycle. Builds agentic QA capabilities, scalable test automation, CI/CD quality controls, intelligent testing, and continuous verification. Partners with engineering, DevOps, architecture, and product teams while leading quality engineers and automation specialists. Applies generative AI, machine learning, and intelligent automation to improve test design, execution, defect prevention, release readiness, and software quality.

Own predictive intelligence for sales, marketing, and medical workflows by developing predictive scores, models, rules, and decision logic. The role uses Salesforce Data Cloud, CRM data, and external data to support next-best-action use cases, embeds predictions into CRM workflows, monitors model performance, and ensures compliance with medical, legal, and privacy requirements. The analyst collaborates with business teams, Salesforce, system integrators, and AI teams to improve predictive capabilities and platform design.

Lead the design and deployment of AI platforms, agentic systems, model gateways, RAG pipelines, and AI-focused DevOps infrastructure. Build self-service GCP AI APIs, SDKs, and Terraform modules; manage model routing, observability, security, deployment, and automation using GKE, Cloud SQL, Cloud Build, and related services. The role requires extensive platform engineering, cloud infrastructure, IaC, MLOps, and enterprise AI architecture experience.

Participate in a 12-week internship collaborating with business and AI teams to identify use cases, prototype and deploy AI solutions using low-code frameworks, large language models, and orchestration tools. Support AI literacy materials, demonstrations, and internal showcases that promote adoption. Translate technical concepts into business value while developing analytical, problem-solving, communication, and collaboration skills.

Lead the architecture and delivery of AI/ML initiatives supporting U.S. Air Force and Army predictive logistics and condition-based maintenance programs. Coordinate engineering teams, translate mission needs into technical solutions, guide tradeoff decisions, mentor technical leaders, and ensure AI/ML systems improve fleet maintenance, aircraft availability, and military readiness. The role requires Databricks expertise, technical leadership, stakeholder communication, and an active Secret clearance.

Monitors and reconciles DenialsAI account data to verify case creation, workflow progression, user activity, and appeal output. Investigates pipeline discrepancies, builds operational reports and dashboards, tracks resolution and coverage metrics, maintains KPI scorecards, defines monitoring thresholds, and validates data accuracy. Collaborates with engineering, operations, client services, and external stakeholders while complying with HIPAA and information security requirements.

Operate and improve an on-premises Kubernetes-based AI and large language model platform across development, QA, and production. Responsibilities include infrastructure deployment, maintenance, troubleshooting, access provisioning, CI/CD support, Ansible automation, monitoring, incident response, documentation, and collaboration with infrastructure, security, and engineering teams.

Designs, deploys, and scales enterprise AI agents, RAG systems, automations, and integrations across ServiceNow and Microsoft ecosystems. Builds solutions with Claude, Copilot Studio, Azure AI Foundry, Azure AI Search, and related orchestration tools. Responsibilities include full-stack development, customer-facing implementation, solution architecture, evaluation, responsible AI controls, troubleshooting, and reusable platform development. The role requires extensive travel and collaboration with technical and business stakeholders.

Owns AI governance submissions from intake through cross-functional review, risk escalation, approval, and compliant implementation. Coordinates Legal, Privacy, Security, Procurement, Cloud, Identity, ServiceNow, and enterprise technology stakeholders; tracks schedules, blockers, documentation, and onboarding requirements. Ensures approved AI products are registered in CSDM, completes post-implementation checks, and improves governance processes, playbooks, and enterprise integrations.

Researches AI tools, platforms, and vendors; assesses privacy, security, transparency, contractual, regulatory, and reputational risks; gathers evidence; prepares governance submissions; validates policy alignment; maintains program tracking; and improves AI governance processes in collaboration with legal, security, privacy, procurement, technology, and business stakeholders.

Freelance contributors record spontaneous Xhosa conversations, participate in speech and AI interaction tasks, annotate recordings, and provide metadata. Work is remote, flexible, and task-based for approximately 2–4 hours daily. Candidates need native-level Xhosa fluency, advanced English, attention to detail, reliable internet, a quiet recording space, and a microphone or headset. Prior speech recording or data annotation experience is advantageous but not required.

Designs and implements manufacturing processes for aerospace engines, supporting design for manufacturability, assembly, and testing. Develops work instructions, process flows, tooling designs, and inspection plans; evaluates machining, welding, brazing, additive manufacturing, and assembly methods. Collaborates with engineering, quality, supply chain, and production teams, performs root-cause analysis and corrective actions, and supports FMEAs, risk assessments, equipment validation, quality compliance, and process optimization using AI and manufacturing engineering tools.

Leads the design, implementation, and optimization of rocket engine manufacturing, assembly, integration, and test processes. Develops work instructions, tooling, fixtures, and production equipment; supports DFM/DFA/DFT, quality systems, root cause analysis, corrective actions, FMEAs, and process validation. Collaborates with engineering, quality, supply chain, and production teams to improve reliability, throughput, cost, and cycle time while meeting aerospace safety and quality standards.

Design and build Python APIs, agentic AI frameworks, LLM-powered clinical documentation systems, and EHR integrations. Evaluate and improve AI output quality for real-world clinical workflows, collaborate with physicians and customers to resolve documentation issues, and contribute across the platform’s full stack. The role requires strong Python, LLM, API, testing, and communication skills, with Google Cloud Platform and Firebase experience preferred.