Assistant Director, Artificial Intelligence, NY

ISDA; New York (NY); On-site; USD 120,000 - 160,000; Full time

Job summary

ISDA in New York is seeking a qualified candidate for a hands-on AI Solutions role. This position will involve architecting and building production AI systems while managing delivery, quality, and partner relations.

The successful applicant should have strong experience in AI product delivery, ideally within financial markets, and demonstrate engineering skills in Python, Java, and AWS technologies. A degree in Computer Science or a related field is preferred.

Qualifications

• 5+ years leading AI-enabled product delivery.
• Experience in Python and Java for production systems.
• Strong knowledge of LLMs and AI model risk controls.

Responsibilities

• Architect and build scalable AI systems.
• Define product requirements and delivery priorities.
• Oversee enhancement of priority AI capabilities.

Skills

AI product delivery

Python

AWS

Java

Stakeholder management

Education

Degree in Computer Science or related

Tools

TypeScript

React

Job description

Overview

This is a hands-on role. The successful candidate will architect and build production AI systems directly, while owning delivery, quality, evaluation, and partner management across the AI Solutions Lab portfolio. The role reports to the Senior Director of Digital Transformation and head of the AI Solutions Lab.

Duties And Responsibilities

• Deliver the next phase of the ISDA AI Solutions Lab’s buildout, helping move current AI initiatives from prototype/MVP stage toward robust, scalable and member-ready delivery. Architect and build the next phase of AI agents, external and internal.
• Own the design and delivery of AI solutions that make ISDA standards and digital solutions more accessible, usable and AI-ready for members.
• Help shape and scale the ISDA Knowledge Base and Assistant as the governed foundation for AI-enabled access to ISDA standards, taxonomies and related IP.
• Oversee enhancement of priority AI capabilities including the CDM Coder, DRR Translator, Tracer, cross-jurisdiction analysis and AI legal opinions initiatives.
• Help drive development and rollout of internal AI capabilities and agents aligned with the internal AI deployment roadmap.
• Define product requirements, broader Agents orchestration, architecture direction, evaluation harnesses and quality standards and delivery priorities across the AI Solutions Lab portfolio.
• Work closely with internal SMEs across CDM, DRR, legal, IT and product teams to ensure solutions are accurate, grounded and useful in real workflows.
• Reach out to members for pulse checks and convert member and stakeholder feedback into roadmap decisions, product refinements and delivery choices to maximize adoption.
• Help define practical connectivity and delivery models, including MCP servers and packaged AI Skills, so members can consume ISDA AI capabilities safely within their own environments.
• Contribute to broader ISDA AI strategy development, including alignment between external member-facing AI solutions and internal AI deployment priorities.
• Lead AI quality, guardrails and governance across the Lab’s solutions, including evaluation harnesses, groundedness and traceability checks, observability and tracing, confidence frameworks, security and safe use boundaries, both internally and externally.
• Own cost aware design of AI workloads, balancing performance and reliability against inference and infrastructure spend.
• Manage relevant external partners and specialist vendors, ensuring work is aligned to ISDA’s priorities, timelines, architecture and ownership model.
• Support the Senior Director including for executive and board reporting by articulating progress, key risks, delivery needs and strategic value in a clear and concise way.
• Help build a durable internal AI capability for ISDA that protects ISDA IP, accelerates adoption of ISDA standards and reinforces ISDA’s strategic position in the market.

Relevant Skills / Abilities

• Strong senior-level experience (at least five years) leading the design and delivery of AI-enabled products or platforms from prototype through controlled rollout and production, with a demonstrable track record of shipping production AI systems that serve real users.
• Hands-on engineering ability in Python (and ideally TypeScript/React for front end UI) and Java, and comfortable building production systems directly.
• Deep understanding of LLMs, retrieval-augmented generation (including hybrid retrieval across semantic, graph and keyword search, with reranking and embedding-model selection), knowledge bases, knowledge graphs and ontologies, agentic workflows and skills, evaluation methods (eval harnesses, LLM-as-judge, groundedness and faithfulness metrics, tracing), and model risk controls.
• Experience building secure, scalable and reliable AI solutions in enterprise environments, including governance, permissions, auditability and data protection including private retrieval architectures and ensuring proprietary data is not exposed to external model providers
• Hands-on AWS experience (Bedrock, Neptune, OpenSearch, Lambda) is very important. Strong engineers able to ramp quickly will also be considered. Cost-aware design of inference and infrastructure spend is expected.
• Proven ability to translate complex domain knowledge into usable AI products, ideally in financial markets, regulatory technology, legal tech, standards or data-intensive environments; or a demonstrated ability to ramp quickly on a complex domain.
• Strong product and solution architecture skills, with the ability to define use cases, prioritize roadmap items and align technical delivery with strategic business outcomes.
• Experience overseeing external vendors, technology partners and proof-of-concept work, while retaining internal control of direction, quality and IP.
• Ability to work closely with subject matter experts to refine AI tools iteratively and turn specialist feedback into practical product improvements.
• Strong grasp of structured data, taxonomies, ontology-style data models and mappings across complex standards or schemas.
• Experience with user testing, controlled pilots, adoption planning, training and feedback loops for specialist user populations.
• Strong judgment on AI risks, including hallucination, groundedness, security, explainability, confidence scoring and safe deployment boundaries.
• Degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related discipline, or equivalent practical experience, is desirable.
• Excellent communication skills, including the ability to understand member issues, to work across the organization and influence and align stakeholders, and to brief senior management and explain technical issues in concise business language.
• Demonstrated ability to operate in a lean, hands-on environment, balancing strategy, execution and stakeholder engagement.