As AI Engineer in an AI Development pod you build the AI solutions that run our redesigned workflows, from first prototype to production, on our shared Azure AI platform. That work ranges from generative AI applications and document processing to AI agents and multi-agent workflows.
Responsibilities
Build AI-powered applications, from LLM assistants and document extraction to AI agents and multi-agent workflows that read documents, pull data, perform checks and prepare work for human review.
Connect AI solutions to our systems and data through APIs, MCP servers and the shared AI platform.
Build the workflow logic, tool integrations, guardrails and human review steps for each workflow.
Write automated tests and evaluations, and fix defects every sprint through testing with users.
Take workflows through pilot and into production, then keep improving them as they scale across funds and clients.
Compensation Range:
Pay Range - Start:
$118,960.00
Pay Range - End:
$178,440.00
Geographic Specific Pay Structure:
Structure 110:
$130,880.00 USD - $196,320.00 USD
Structure 115:
$136,800.00 USD - $205,200.00 USD
We believe in fairness and transparency. It’s why we share the salary range for most of our roles. However, final salaries are based on a number of factors, including the skills and experience of the candidate; the current market; location of the candidate; and other factors uncovered in the hiring process. The standard pay structure is listed but if you’re living in California, New York City or other eligible location, geographic specific pay structures, compensation and benefits could be applicable, click here to learn more.
Responsibilities
Applies and integrates advanced statistical, mathematical, data mining, predictive modeling and business analysis skills and techniques to discover and identify new insights, predict and prescribe outcomes, advise on turning new insights into actionable opportunities and outcomes, and provide the tracking and measurement of results.
Develop LLM-based, mathematical models, algorithms, machine learning techniques, and robust analytics to support analytic insights and visualization of complex data sets for productization and monetization.
Create evaluation frameworks and monitor deployed models and AI systems for performance, drift and unintended outcomes.
Applies creative problem solving and inter-departmental networking to address data and information needs across the enterprise.
Shares best practices with peers through coaching and mentoring core methodologies, patterns, standards and processes.
A technical role focused on building and advancing AI-native agentic harnesses, multi-agent workflows, and learning systems for professional services and legal firm platforms.
Compensation
Base salary: $250,000 to $400,000 per year
Responsibilities
Advance our multiplayer agentic harness so humans, agents, firm systems, and clients can collaborate on shared work with the right context, permissions, and accountability.
Design multi-agent workflows using orchestration and actor models so agents can divide work, coordinate with people and other agents, and recover when plans change.
Build shared task and state management so work moves reliably between agents, attorneys, clients, and firm systems without losing context or ownership.
Make agents more effective across software through computer use and deep integrations with the systems a professional services firm depends on.
Turn expert interactions into learning signals by capturing how people delegate, correct, and review work, along with the context behind their decisions.
A senior individual-contributor leadership role defining and driving the architecture of AI and agentic systems across multiple teams and product domains, turning experimental AI capabilities into reliable production systems.
Locations (2)
Boca Raton, Florida, United States
Hyderabad, Telangana, India
Responsibilities
Define and drive technical direction for AI and agentic systems, and contribute to the AI platform roadmap across teams
Influence architecture decisions for compute, cloud, and AI infrastructure across teams
Lead the design of large-scale AI/LLM systems: inference platforms, APIs, and distributed architectures
Architect production multi-agent systems end-to-end: orchestration, state management, tool integration, and failure handling
Define and drive best practices and standards for AI/LLM systems across teams (agent design, evaluation, observability, reliability)
As Staff Product Engineer, you will translate our core technology into the web-based products where players discover and engage with games, and where partners extend them to their audiences. You will hold end-to-end ownership of the products you lead.
Compensation
Competitive salary and equity
Responsibilities
Take end-to-end ownership of the products you lead, from brief through implementation, integration, testing, rollout and iteration across frontend, backend, APIs, data and partner integrations.
Make practical architecture decisions for the web client and application services, and work with our core technology team to turn platform capabilities into polished, responsive experiences.
Design and own the cloud foundations and production operations behind our products: infrastructure as code, environments, fast build and release pipelines, observability, capacity and cost, with dependable rollback and recovery.
Set clear performance budgets and release criteria, keep every experience responsive and reliable across devices and browsers, and remove bottlenecks as usage grows.
Build instrumentation, experimentation and rollout controls into the product so the team can trust the data, measure impact and learn from every release.
The Staff Software Engineer role is a rare chance to shape the core systems of a high-growth startup that's breaking barriers in its third record-setting year. We're looking for a senior technical leader who does their best work hands-on: someone who takes on the hardest problems, writes code that sets the standard for others, and helps whole teams get better. Shipwell is an AI-forward engineering organization.
Responsibilities
Own the design, build, and ongoing health of critical systems and services on the Shipwell platform.
Write high-quality, well-tested, production code, and spend most of your time building.
Use AI agents and multi-agent workflows day to day to speed up code generation, code review, and QA testing, while keeping quality high.
Build and share custom agents, establishing / reviewing projects AI Harness, and workflows that boost your own productivity and your team's.
Help set how Shipwell engineers use AI, including best practices, guardrails, and ways to measure its impact on speed and quality.
Requirements
BS/MS/Ph.D. in Computer Science or a related field
Lead the design, development and deployment of Agentic AI solutions for test, operating and scaling AI solutions on cloud platforms, and drive test analysis for 5G and 6G RAN features.
Compensation
The salary range for this position is 69,000 - 86,000 CAD
Responsibilities
Drive the design, development and deployment of Agentic AI solutions for test
Deploy, operate and scale AI solutions on AWS or other cloud platforms
Drive test analysis of 5G and 6G RAN features
Identify impact and risks of new features on test tools
Educate and support the organization on test strategy
Requirements
M.Sc/B.Sc in Telecommunication/Electrical Engineering/Computer Science or equivalent
Lead the design and engineering of agentic AI solutions for State Street Investment Management’s Data, Analytics & AI Services team.
Compensation
Salary Range: $120,000 - $202,500 Annual
Responsibilities
Lead an agile agentic AI engineering team to deliver scalable solutions that meet evolving business and client needs.
Partner with global stakeholders to execute cross-border initiatives and continuously strengthen engineering standards and best practices.
Coach and mentor junior agentic engineers, building a culture of continuous learning, accountability, and high performance.
Design agentic solution and implementation, including agent workflows; agent enablement across platform components; and governance (registration, security, observability, and monitoring) for AI agents.
Design and lead the implementation of agentic AI capabilities, including architecture patterns, best practices, framework and tool selection, development, integration, and deployment.
Requirements
Bachelor’s degree in Computer Science
Nice to have: Agentic Engineer experience within a financial institution
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