Summary

You have 3+ years in LLM/AI/ML, experience with Salesforce/Workday, AWS cloud, Python, Docker, database architectures, NLP libraries, and strong communication skills.
You will design and implement automated workflows, integrate ML/NLP models, manage data pipelines, mentor team members, and ensure quality outputs through KPI tracking and the software development lifecycle.

Join FactSet's Enterprise Solutions and Intelligence team as a Lead Software Engineer to drive forward-thinking innovations in our internal corporate systems as part of our Internal AI initiative. Your extensive expertise will be vital in deploying state-of-the-art solutions to automate workflow tasks and generate insight summaries from CRM (Salesforce), HCM (Workday), bug tracking (ServiceNow), usage logs and various other billing, entitlement, pricing, revenue tracking, marketing systems. This role is perfect for someone with a passion for tackling complex problems in the corporate tools domain with a desire to interact with end users & stakeholders and has a proven ability to deliver robust, high-performance AI systems.

Key Responsibilities

Architect groundbreaking agentic workflows tailored to task automation within inhouse, and 3rd party licensed software service eco-systems.
Vet, select and implement Agentic Workflow Framework for task automation and define specifications for integration capabilities for internal developers.
Implement agents within selected frameworks to automate various repetitive manual tasks and summarize data out of corporate tools in concise human readable form.
Design insight generation techniques that summarize key highlights from large complex datasets and support natural language prompts for deep-dive analysis.
Construct and maintain robust data pipelines capable of processing complex structured and unstructured quantitative and textual data, ensuring high quality inputs for our models.
Work closely with data scientists and ML engineers to integrate and manage diverse ML and NLP models within production environments effectively.
Maintain KPI-oriented mindset for prioritizing, executing and measuring success of output.
Manage full software development lifecycle from initial design/coding and test/deployment.
Act as a leader and mentor to team members, promoting a culture of innovation and continuous learning within the team.

Minimum Requirements

3+ years of software engineering experience, significantly focused on LLM/AI/ML solutions.

Critical Skills

Experience working with the Salesforce and Workday technology stacks, including platforms like AgentForce and Einstein.
Familiarity with Agentic Workflow frameworks, such as LangChain/Graph, AutoGen, Swarm, and MetaGPT.
Demonstrated expertise in cloud architecture, particularly with AWS, including managed services.
Strong understanding of Natural Language Processing, Machine Learning, and Deep Learning fundamentals, with a proven track record in model development and deployment.
Proficiency in Python, complemented by strong skills in Docker and API development.

Additional Skills

Knowledge of major database architectures, including SQL, NoSQL, and Vector databases.
Experience with Knowledge Graphs and the ability to architect LLM-powered solutions.
Expertise in NLP libraries, such as NLTK and SpaCy, and proficiency in analyzing unstructured text.
Excellent communication skills, enabling effective engagement with both technical and business audiences, as well as leading cross-functional projects.

Education

Bachelor’s degree in computer science

The budgeted salary range for this position in the states of Connecticut and New York is $175,000.00 – 190,000.00

At FactSet, we celebrate diversity of thought, experience, and perspective. We are committed to disrupting bias and a transparent hiring process. All qualified applicants will be considered for employment regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status. FactSet participates in E-Verify

FactSet is an Equal Opportunity Employer – M/F/Veteran/Disability/Sexual Orientation/Gender Identity

Requirements

3+ years of software engineering experience, significantly focused on LLM/AI/ML solutions.
Experience working with the Salesforce and Workday technology stacks, including platforms like AgentForce and Einstein.
Familiarity with Agentic Workflow frameworks, such as LangChain/Graph, AutoGen, Swarm, and MetaGPT.
Demonstrated expertise in cloud architecture, particularly with AWS, including managed services.
Strong understanding of Natural Language Processing, Machine Learning, and Deep Learning fundamentals, with a proven track record in model development and deployment.
Proficiency in Python, complemented by strong skills in Docker and API development.
Knowledge of major database architectures, including SQL, NoSQL, and Vector databases.
Experience with Knowledge Graphs and the ability to architect LLM-powered solutions.
Expertise in NLP libraries, such as NLTK and SpaCy, and proficiency in analyzing unstructured text.
Excellent communication skills, enabling effective engagement with both technical and business audiences, as well as leading cross-functional projects.
Bachelor’s degree in computer science.

Responsibilities

Architect groundbreaking agentic workflows tailored to task automation within inhouse, and 3rd party licensed software service eco-systems.
Vet, select and implement Agentic Workflow Framework for task automation and define specifications for integration capabilities for internal developers.
Implement agents within selected frameworks to automate various repetitive manual tasks and summarize data out of corporate tools in concise human readable form.
Design insight generation techniques that summarize key highlights from large complex datasets and support natural language prompts for deep-dive analysis.
Construct and maintain robust data pipelines capable of processing complex structured and unstructured quantitative and textual data, ensuring high quality inputs for our models.
Work closely with data scientists and ML engineers to integrate and manage diverse ML and NLP models within production environments effectively.
Maintain KPI-oriented mindset for prioritizing, executing and measuring success of output.
Manage full software development lifecycle from initial design/coding and test/deployment.
Act as a leader and mentor to team members, promoting a culture of innovation and continuous learning within the team.

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AI Automation Lead Software Engineer - LLM/AI/ML Solutions.