Top AI & Machine Learning Jobs

Two-year development program for recent graduates working on AI, automation, data analytics, and digital transformation initiatives. Responsibilities include developing intelligent agents and workflow automations, translating business needs into requirements and user stories, analyzing performance data, testing and deploying AI solutions, documenting processes, supporting adoption, and evaluating emerging technologies. The role collaborates across technology, product, business, operations, and IT teams in a regulated commercial real estate environment.

Leads enterprise AI engineering strategy, architecture, platform development, governance, security, deployment, and operations. Builds scalable AI infrastructure and reusable services for foundation models, agentic systems, RAG, and machine learning applications. Evaluates emerging technologies, establishes enterprise standards and guardrails, manages lifecycle and costs, drives responsible AI adoption, and leads engineering and architecture teams through enterprise transformation.

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.

Advises enterprise executives on AI transformation for contact center and customer service operations. Develops AI strategies, roadmaps, business cases, operating models, and value realization frameworks. Leads executive workshops and defines use cases involving virtual agents, agent copilots, analytics, automation, and agentic AI. Evaluates platforms and technologies, provides vendor-neutral recommendations, and partners with clients, vendors, and delivery teams to guide successful implementation.

Own the architecture, engineering quality, security, governance, observability, and reliability of enterprise AI client builds across Azure, AWS, and Google Cloud. Lead client technical engagements, security and procurement reviews, solution scoping, reusable product development, and technical thought leadership. Build and grow the engineering team, establish standards, and guide AI-first workflows across a project-based consultancy environment.

Build and maintain automated API, integration, and end-to-end tests for AI agents and critical workflows. Evaluate agent task completion, response quality, tool usage, permissions, and changes to models, prompts, and context. Integrate quality checks into CI/CD, convert production defects into regression tests, use AI to explore workflows and reproduce bugs, and share testing methods with AI and QA teams.

Lead research and thought leadership on data management and AI readiness, produce actionable insights, advise clients and sales, present at events, mentor analysts, and improve research processes to drive client outcomes.

Develop and operationalize statistical, mathematical, geospatial, and data science models supporting CBP risk management and data-driven operational decisions. Responsibilities include exploratory data analysis, regression modeling, suitability modeling, GIS analysis, and scripting with Python, SQL, and R. The role requires independent analytical work, ArcGIS experience, and the ability to obtain TS/SCI clearance and DHS suitability.

Build and operate LLM-powered features, agentic workflows, NLP pipelines, and event-driven backend services for insurance claims. Responsibilities include designing evals and guardrails, implementing semantic search and structured outputs, modeling relational, document, and graph data, tracing model calls, enforcing privacy and security, writing technical designs, and participating in on-call support.

Architect and build AI reasoning systems, agentic workflows, and multimodal intelligence pipelines for regulatory, financial, and spatial analysis. Develop production-grade LLM applications, integrate validation and evaluation frameworks, process scanned documents and schematics, and own AI-powered features across models, backend workflows, and customer-facing interfaces. The role emphasizes reliability, observability, autonomous ownership, and full-stack product development within a remote founding team.