AI Engineering Lead

🔥 12 hours ago

Apply Now
Find Similar Remote Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Logo of IMA Financial Group, Inc.

IMA Financial Group, Inc.

1001 - 5000 employees

Founded 1980

💸 Finance

🏢 Enterprise

💰 Private Equity Round on 2020-11

Finance • Insurance • Enterprise

IMA Financial Group, Inc. is a diversified financial and insurance services company providing specialized insurance solutions across various industries, including agribusiness, construction, digital risk, education, energy, healthcare, hospitality, life sciences, manufacturing, marine, private equity, real estate, and technology. The company offers a wide range of insurance services such as business insurance, employee benefits, personal insurance, retirement solutions, wholesale insurance, wealth management, and more. IMA is committed to protecting assets and foreseeing challenges, ensuring that clients are prepared for the future. They emphasize community impact, philanthropy, and customer-driven solutions, supporting both innovation and community betterment.

📋 Description

• Design, build, and deploy production-grade end-to-end AI solutions, including workflow automation agents, RAG pipelines, and copilots embedded in business workflows, and LLM-driven applications • Translate business needs into technical designs and working products to deliver usable, high-impact solutions, not just proofs of concept • Architect and implement AI-assisted data workflows and agentic systems • Build and maintain LLM-enabled services, prompt frameworks, and coding standards • Develop semantic/context layers ensuring AI outputs align with business logic and data models • Design multi-agent workflows, including human-in-the-loop controls • Make pragmatic tradeoffs to ship quickly while maintaining long-term sustainability • Create scalable patterns for prompt design & orchestration, agent-based workflows, and API integrations & data access • Inform architecture decisions for AI systems balancing speed, security, scalability, maintainability, and cost • Help establish engineering standards and best practices for applied AI across the organization • Establish reusable components, frameworks, and templates to accelerate AI development • Integrate AI automation with enterprise systems, APIs, and data platforms • Evaluate and recommend tooling across the stack (models, frameworks, vector stores, orchestration layers) • Define data requirements and, when needed, build or extend data pipelines to ensure AI systems have reliable, production-ready inputs • Design and implement evaluation frameworks to define and track AI system performance, including task success, accuracy, latency, cost, and business impact; establish feedback loops to continuously improve quality, reliability, and cost-efficacy in production environments • Build guardrails and validation layers to reduce hallucinations, enforce structured outputs, and ensure safe system behavior • Establish monitoring and observability across AI systems (performance, usage, cost, latency, failure modes) • Implement modern engineering practices including CI/CD, versioning, rollback strategies, and automated testing • Ensure solutions meet security, compliance, and governance requirements in a regulated environment • Partner with business leaders, operations & service teams, and product stakeholders to shape use cases and turn them into working solutions • Work closely with AI Enablement to refine workflows and improve adoption • Drive fast iteration cycles, quickly moving from idea to working solution to scaled implementation; iterate solutions based on real user feedback and usage patterns

🎯 Requirements

• 7-10+ years in software engineering, data engineering, or AI/LLM experience • Hands-on experience building and deploying production AI systems • Hands-on experience building applications using LLMs and modern AI tooling • Experience with cloud platforms (Azure preferred), Python, APIs, containerization, and CI/CD practices • Experience building RAG pipelines, agent-based workflows, or orchestration layers • Experience with vector databases, embedding pipelines, and retrieval systems • Strong problem-solving ability and bias toward practical, efficient solutions; ability to operate in a fast-moving, ambiguous environment • Experience translating business needs into technical solutions

🏖️ Benefits

• Annual Performance Bonus • Stock Purchase • Medical Plans • Prescription Drugs • Dental • Vision • Family Assistance Program • FSA • HSA • Pre-Tax Parking Plan • 401(k) • Life/AD&D • Accident • Critical Illness • Hospital Indemnity • Long Term Care • Short-term Disability • Long-term Disability • Business Travel Accident • Identity Theft • Paid Time Off • Flexible Work Options • Paid Holidays • Sabbatical • Gift Matching • Well-Being Stipend • Personal and Professional Development

Apply Now

Similar Jobs

🔥 13 hours ago

Guidehouse

10,000+ employees

Lead AI Software Engineer developing scalable AI-enabled solutions for federal clients. Collaborating with cross-functional teams to deliver high-impact applications on AWS.

AWS

Cloud

Distributed Systems

Java

Microservices

MySQL

Postgres

Python

RDBMS

React

🔥 14 hours ago

Genesys

5001 - 10000

🤖 Artificial Intelligence

☁️ SaaS

📡 Telecommunications

Agentic AI Architect responsible for designing and delivering AI-powered customer experience solutions. Collaborating with enterprise organizations to enhance customer experience using AI technologies.

AWS

Azure

Cloud

Google Cloud Platform

🔥 16 hours ago

LeoLabs

51 - 200

🚀 Aerospace

🔧 Hardware

☁️ SaaS

Senior AI Engineer developing AI and machine learning systems for LeoLabs' space domain awareness. Designing scalable solutions and driving insights from large-scale data in aerospace context.

Python

PyTorch

Scikit-Learn

Spark

SQL

Tensorflow

🔥 17 hours ago

Particle41

51 - 200

☁️ SaaS

🤖 Artificial Intelligence

🏢 Enterprise

AI Engineer at Particle41 leading development of machine and deep learning models. Collaborate with teams to deploy scalable AI solutions.

Cloud

Microservices

Python

PyTorch

Scikit-Learn

Tensorflow

🔥 19 hours ago

EnCharge AI

11 - 50

🤖 Artificial Intelligence

🔧 Hardware

🤝 B2B

Research Engineer pushing AI model quality and efficiency at EnCharge AI. Building fine-tuning pipelines and benchmarking frameworks while collaborating closely with hardware teams.

Python

PyTorch