Analyst, AI Automation

Antares Capital•Chicago, NY

21h•$85,000 - $105,000•Hybrid

About The Position

Reporting to Technology leadership, the AI Automation Analyst will support the execution of AI-driven initiatives while contributing to the Technology PMO’s portfolio coordination and governance processes. This role can be based in our New York or Chicago office. This role is designed for an early-career technologist with hands-on AI and automation skills who is eager to build intelligent workflows, develop AI agents, and improve execution discipline across the Technology organization. The position combines technical AI development with structured PMO support to ensure scalable, governed, and business-aligned delivery. As part of Antares’ evolving AI transformation journey, this role provides exposure to enterprise AI architecture, governance standards, and PMO practices within a structured financial services environment. This is an ideal opportunity for someone looking to deepen their AI engineering skills while gaining visibility into how technology strategy and execution are managed at scale.

Requirements

Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, or related field.
2–4 years of experience in AI, automation, analytics, software engineering, or technical analyst roles.
Strong analytical and problem-solving skills.
Ability to build prototypes quickly while maintaining structured documentation and governance awareness.
Strong written and verbal communication skills, with the ability to prepare clear summaries for both technical and non-technical audiences.
Comfort working cross-functionally across Technology, Risk, Cyber, and Business teams.
Python (required)
SQL (required)
APIs and data integration
LLM platforms and prompt engineering
Integrity: Upholding ethical standards and honesty in all interactions.
Problem Solving: Analyzing challenges and finding practical solutions.
Adaptability: Flexibility in adjusting to changing circumstances.
Time Management: Efficiently organizing and prioritizing tasks.
Analytical Thinking: Evaluating data and drawing meaningful conclusions.
Customer Service: Providing excellent service to clients or customers.
Technical Proficiency: Mastery of relevant software, tools, or technologies.
Project Management: Successfully planning, executing, and monitoring projects.
Must have unrestricted authorization to work in the United States.
Must be willing to comply with pre-employment screening, including but not limited to drug testing, reference verification, and background check.
Must be willing to work from the New York or Chicago office.

Nice To Haves

Familiarity with Azure, Databricks, or similar data platforms preferred.
Experience working in financial services or regulated environments (preferred).
Exposure to Agile or hybrid project delivery methodologies (preferred).
MS Fabric (preferred)
RAG concepts and vector databases (preferred)

Responsibilities

Design, build, and maintain lightweight AI agents and automation workflows to improve Technology and PMO processes.
Develop retrieval-augmented generation (RAG) pipelines, prompt-based workflows, and internal copilots using modern LLM platforms.
Automate repetitive operational tasks such as meeting summary generation and action tracking, status report roll-ups, intake triage and intelligent routing, approval reminders and workflow notifications.
Create reusable prompt libraries and structured templates to improve output consistency and governance.
Build simple APIs, scripts, or low-code automations (Python, Power Automate, etc.) to integrate AI tools with internal systems (e.g., ServiceNow, SharePoint, Monday.com).
Test, validate, and monitor AI outputs for accuracy, explainability, and risk alignment, escalating issues appropriately.
Adhere to enterprise AI governance, security, and data privacy standards when developing automation solutions.
Participate in AI risk assessments and model documentation processes as required.
Document technical design, assumptions, and controls in accordance with internal AI governance standards.
Partner with senior AI engineers, architects, and business stakeholders to translate use cases into technical requirements and actionable development tasks.
Support data preparation, transformation, and basic feature engineering activities for AI and analytics initiatives.
Assist with model evaluation, prompt tuning, and output validation to ensure reliable performance.
Contribute to experimentation and rapid prototyping of AI use cases across the organization while maintaining appropriate documentation and version control.
Participate in working sessions with business stakeholders to clarify objectives, success metrics, and operational constraints.
Maintain version control and documentation for scripts, workflows, and automation assets.
Develop automated dashboards and reporting solutions to enhance portfolio transparency and decision support for leadership.
Support tracking of initiative KPIs, benefits realization metrics, and AI use case value measurement.
Prepare governance materials and executive-ready summaries using AI-assisted workflows to improve consistency and timeliness.
Track action items and support structured follow-up to reinforce accountability and delivery discipline.
Help improve PMO processes by identifying automation opportunities, standardizing templates, and eliminating manual steps where appropriate.
Support maintenance of the Technology Book of Work, including tracking milestones, risks, dependencies, and status updates across AI and broader Technology initiatives.
Assist with initiative intake documentation, requirements clarification, and backlog grooming for AI and analytics initiatives.