Top Artificial Intelligence Jobs

Leads development of secure, scalable Java and AWS software systems, including microservices, event-driven platforms, and production machine-learning systems. Designs data and feature pipelines, model deployment and monitoring, automation, CI/CD, and operational stability practices. Guides code reviews, testing, secure coding, vendor evaluations, and responsible adoption of AI-assisted engineering tools. Collaborates across product, data, platform, SRE, and governance teams while promoting MLOps, LLM, observability, and model-monitoring practices.

Develops secure, scalable full-stack applications for Asset Management. Responsibilities include software design, coding, testing, troubleshooting, architecture, data analysis, visualization, and operational stability. Uses enterprise-authorized AI coding tools responsibly to improve development productivity while validating outputs for security and correctness. Builds services with Hibernate, Spring JPA, PostgreSQL, REST APIs, and GraphQL, with preferred experience in Kafka, Avro, React, and AWS.

Lead architecture and hands-on delivery of production-grade LLM and agentic AI platforms on AWS. Design retrieval/RAG, agents, guardrails, tooling, observability, and APIs. Optimize performance, cost, and security; establish evaluation and testing frameworks; mentor engineers and drive cross-team technical standards in a regulated enterprise.

Lead design, development, and production deployment of advanced AI/GenAI and LLM solutions. Build and tune models, integrate generative AI into ML platforms, drive MLOps adoption, ensure responsible AI governance, collaborate cross-functionally, and mentor AI engineers.

Build and lead production Python software for technology-risk oversight, including data pipelines, PostgreSQL systems, authenticated APIs, and LLM agent workflows. Develop RAG, tool orchestration, evaluation, and guardrails; ensure security, auditability, observability, testing, reliability, and responsible AI use. Collaborate with Product, Risk, Controls, Compliance, and data teams while delivering dashboards and evidence packages.

Lead design, development, and production deployment of AI, GenAI, and LLM solutions. Build and tune models in Python, collaborate across product and engineering, drive MLOps adoption, ensure model governance and regulatory compliance, and communicate results to technical and business stakeholders.

Leads full-stack development of secure Private Banking applications and production-grade agentic AI solutions. Builds systems using Python, Java, LLMs, orchestration frameworks, APIs, cloud services, and event-driven architectures. Drives AI-assisted engineering governance, responsible AI practices, security, observability, automation, and production readiness. Collaborates with product, architecture, cybersecurity, data, and business teams; mentors engineers and influences technical direction across globally distributed agile teams.

Lead and manage cross-firm AI in Operations program initiatives: develop strategic plans, apply structured problem-solving and design thinking, support multiple workstreams, engage senior stakeholders, standardize AI use cases, and drive scaling and reimagination of AI capabilities across operations.

Lead engineering for production-grade agentic AI and LLM platforms. Design AWS cloud-native services, RAG solutions, vector storage, agent memory, APIs, and microservices. Establish MLOps, monitoring, governance, security, observability, and responsible AI practices. Provide technical direction, make architecture decisions, review code, mentor engineers, and drive adoption of AI-assisted development standards across teams in a regulated enterprise environment.

Design, build, and operate AI-enabled applications and ML/LLM platforms. Deliver production-quality code, SDK/REST integrations, MLOps pipelines, model/versioning and CI/CD, distributed fine-tuning and evaluation, and reusable platform components. Drive adoption of agentic AI workflows, enforce responsible AI and security controls, automate reliability, and influence senior stakeholders to align platform roadmaps with business outcomes.

Lead a global agile scrum team to design, build, and operate scalable, secure microservice-based applications. Integrate AI (Claude Code) into development and delivery, drive architecture and technical decisions, mentor engineers, enforce AI-assisted engineering governance, and ensure production quality, stability, and automation across the SDLC.

Lead cross-functional programs to design and automate AI/ML governance for generative and agentic models. Develop program plans, risk mitigation, scalable controls, playbooks, and stakeholder alignment to accelerate model lifecycle delivery while ensuring compliance, quality, and responsible AI practices.

Lead design, develop, and deploy secure, scalable full-stack applications (Java or Python) for finance planning and analysis. Drive architecture reviews, operational stability, CI/CD automation, cloud-native AWS deployments, and integration of AI/ML/LLM capabilities. Mentor teams and lead engineering communities of practice.

Lead design, develop, and maintain secure, scalable data and AI-driven systems. Build data pipelines on AWS/Databricks, write production code, drive AI-assisted engineering adoption, enforce validation/security standards, and mentor teams on responsible AI practices.

Summer Analyst in Data & AI will design and build end-to-end data, analytics, and ML/AI solutions using cloud and modern tooling. Responsibilities include developing models and pipelines, running experiments tied to business KPIs, supporting data governance and compliance, creating dashboards, and collaborating in agile teams while receiving mentorship and training.

Lead design and delivery of secure, scalable AI/ML and generative/agentic solutions: develop LLMs and agent frameworks, productionize end-to-end models, mentor teams, collaborate with stakeholders, and drive R&D and PoCs to production.

Lead design, build, and deploy production-scale generative AI and ML solutions. Define semantic modeling strategy and unified semantic layer, create ontologies, integrate semantics across pipelines and APIs, enable ontology-driven intelligent workflows, and implement model training, monitoring, governance, and responsible AI practices while partnering with stakeholders.

Lead enterprise architecture and engineering strategy for AI-native, cloud-native platforms. Define AI-enabled patterns, governance, and guardrails; drive platform modernization, CI/CD, IaC, automated testing, reuse-first engineering, and mentor architect-engineers while ensuring security, resiliency, and auditability.

Lead design, architecture, and delivery of full-stack, AI-enabled applications. Provide technical leadership across frontend, backend, APIs, databases, and AI integration. Drive engineering best practices, CI/CD, automated testing, cloud-native (AWS) solutions, and adoption of AI-assisted development while ensuring secure, resilient, scalable systems.

Deploy and support computer vision systems at customer sites, including provisioning Linux edge computers, NVIDIA Jetson devices, cameras, networks, and modems. Conduct site assessments, install and validate equipment, coordinate contractors and customer IT teams, manage inventory and shipping, monitor systems, troubleshoot incidents, and document procedures. The role requires regular U.S. travel, occasional off-hours work, physical equipment handling, and clear customer communication.

Own People Operations and Employee Relations across payroll, benefits, leave, compliance, onboarding, offboarding, investigations, performance management, and exits. Implement and manage Paylocity as the HR system of record, ensure accurate multi-state and international processes, coach managers through employee issues, and automate repetitive workflows using AI and connected systems.

Build and support production full-stack applications with accessible interfaces, APIs, databases, workflow automation, and AI capabilities. Develop LLM integrations, RAG pipelines, vector search, and agentic workflows while validating AI-generated code. Apply secure development, accessibility, automated testing, CI/CD, MLOps, adversarial AI testing, monitoring, incident response, and Responsible AI practices. Collaborate in Agile sprints and support federal customer requirements.

Leads enterprise AI architecture for a global Audit & Assurance application portfolio. Designs agentic systems, RAG, knowledge graphs, multi-agent orchestration, AI platforms, distributed systems, and cloud-native SaaS architectures. Establishes engineering standards, governance, evaluation, safety frameworks, and reusable platform capabilities while prototyping, reviewing code, coaching teams, and guiding implementation across products and regions.

Leads strategic enterprise sales pursuits involving Dynamics 365, Copilot, and agentic AI. Partners with field, engineering, and go-to-market teams to qualify opportunities, develop value narratives, validate business cases, guide technical and business conversations, and shape solution positioning, sales guidance, and adoption strategies for major customers across government, retail, financial services, and healthcare.

Leads strategic enterprise sales pursuits involving Dynamics 365, Copilot, and agentic AI. Shapes competitive positioning, business value, solution strategies, technical validation, and customer decision criteria. Coordinates account teams, engineering, product, marketing, partners, and field stakeholders to remove blockers and advance complex opportunities. Develops competitive intelligence, enables sellers through coaching and readiness programs, and translates AI and business application capabilities into measurable customer outcomes, revenue, adoption, and usage.