Applied AI Engineer (1042) - Department Of Technology

Applied Ai Engineer

We are a small, mission-driven team leading responsible AI adoption across City government within the Department of Technology (DT).

We work on:

1. Testing and making self-service AI tools available to other departments,
2. Setting technical standards for safe and responsible AI use, and
3. Building and experimenting with prototypes that demonstrate the potential of applied AI.

As our Applied AI Engineer, your primary focus will be designing and backend AI cloud infrastructure needed to power AI services. This includes building ingestion pipelines, managing vector databases, integrating LLM APIs, and ensuring backend systems are reliable, observable, scalable, and safe.

This role is hands-on, creative, and highly collaborative — ideal for someone who enjoys working at the intersection of technology, product, and impact.

Key responsibilities include:

• Build and manage RAG infrastructure and other cloud tools as needed (e.g., ingestion pipelines, embedding services, retrieval APIs, orchestration).
• Deploy and maintain vector databases and integrate them with AI services.
• Develop APIs and backend services that connect prototypes to LLMs and retrieval systems.
• Implement observability practices including monitoring, logging, alerting, and performance metrics to ensure system reliability and transparency.
• Use frameworks like LangChain, LlamaIndex, and related libraries to orchestrate retrieval workflows, agents, and hybrid pipelines.
• Ensure system scalability and resilience, with production-ready practices.
• Collaborate with the AI Product Engineer to integrate backend services with front-end applications and user pilots.
• Contribute to standards for safe, responsible AI adoption (data governance, security, and compliance).
• Experiment with new backend, platform, and cloud tools to stay current with the fast-evolving AI ecosystem.

Education:

An associate degree in computer science, computer engineering, information systems, or a closely related field from an accredited college or university OR its equivalent in terms of total course credits/units [i.e., at least sixty (60) semester or ninety (90) quarter credits/units with a minimum of twenty (20) semester or thirty (30) quarter credits/units in one of the fields above or a closely-related field].

Experience:

One (1) year of experience analyzing, installing, configuring, enhancing, and/or maintaining the components of an enterprise network.

Additional experience as described above may be substituted for the required degree on a year-for-year basis (up to a maximum of two (2) years). One (1) year is equivalent to thirty (30) semester units/forty-five (45) quarter units with a minimum of 10 semester / 15 quarter units in one of the fields above or a closely related field.

Completion of the 1010 Information Systems Trainee Program may be substituted for the required degree.

Desirable qualifications:

• Strong experience with backend/platform engineering
• Experience building and managing RAG pipelines using vector databases and orchestration frameworks (LangChain, LlamaIndex, LangGraph).
• Hands-on experience with observability practices and tools
• Knowledge of cloud platforms (AWS, GCP, or Azure) and containerized deployments
• Ability to work collaboratively in a small, cross-functional team and move quickly on pilots.

Nice-to-have skills:

• Knowledge of search and ranking techniques (hybrid search, rerankers).
• Familiarity with data security, privacy, and compliance in government or regulated contexts.
• Background in ML/AI infrastructure (model serving, caching, fine-tuning workflows).
• Experience contributing to technical documentation and standards.

Who you are:

• Motivated by public impact and eager to shape how AI can responsibly improve services for residents.
• A builder and experimenter who takes a human-centered approach and loves creating prototypes that make AI real and useful.
• Excited by the challenge of making AI safe, transparent, and practical in government.
• Flexible and collaborative, comfortable stepping outside your core skill set to help the team succeed.
• Keen to stay current with emerging technologies

Note: Applicants must meet the minimum qualification requirement by the final filing date unless otherwise noted.

One-year full-time employment is considered equivalent to 2000 hours (2000 hours of qualifying work experience is based on a 40-hour work week). Any overtime hours that you work above forty (40) hours per week are not included in the calculation to determine full-time employment.