At Epiq, your work contributes to complex, global legal outcomes. You’ll join a values‑driven community where integrity guides decisions, relentless service sets the bar, and we thrive on big challenges together. We invest in your growth with enterprise‑wide learning and mobility. We celebrate who you are, and we respect life beyond work with flexibility that’s recognized externally. Enabled by modern platforms and AI, you’ll do the most meaningful work of your career and see your impact at scale.
Job Description:
Summary
We are seeking a highly skilled Lead Software Engineer - AI Solutions with strong expertise in Full Stack Software Development, Solution Design, Cloud Engineering, Data Engineering, and AI application development.
This is a hands-on technical leadership role for an experienced engineer who combines deep software engineering expertise with the ability to lead the design and delivery of scalable, enterprise-grade solutions. The ideal candidate will provide technical direction, mentor engineers, and drive the successful implementation of modern AI-powered applications while remaining actively involved in architecture, development, and problem-solving activities.
As a Lead Software Engineer, you will work closely with Product Owners, business stakeholders, architects, data engineers, DevOps teams, and software engineers to design, build, and maintain scalable products and AI solutions. You will play a critical role in translating business requirements into technical solutions, driving engineering best practices, and ensuring successful delivery of complex initiatives.
Key Responsibilities
- Lead the design, development, and delivery of scalable enterprise applications, APIs, and services.
- Drive technical solution design and contribute to architectural decisions across products and platforms.
- Collaborate with Product Owners and stakeholders to translate business requirements into scalable technical solutions.
- Provide technical leadership and guidance to engineering teams throughout the software development lifecycle.
- Lead design reviews, code reviews, and technical discussions to ensure engineering quality and consistency.
- Design and implement microservices, integrations, reusable frameworks, and cloud-native applications.
- Ensure software solutions meet security, compliance, performance, scalability, and reliability requirements.
- Partner with DevOps teams to implement CI/CD pipelines, deployment automation, observability, and operational best practices.
- Drive continuous improvement initiatives related to software architecture, development standards, testing, and operational excellence.
- Mentor and coach Associate and Senior Software Engineers while fostering a culture of collaboration, innovation, and engineering excellence.
- Evaluate emerging technologies and recommend improvements that enhance product capabilities and development efficiency.
- Act as the primary technical point of contact for delivery teams and provide guidance for resolving complex technical challenges.
AI Responsibilities
- Lead the design and implementation of AI-powered applications and intelligent automation solutions.
- Design scalable Retrieval-Augmented Generation (RAG) architectures and enterprise knowledge retrieval solutions.
- Build and deploy AI-enabled services leveraging Large Language Models (LLMs), vector databases, and AI orchestration frameworks.
- Define engineering standards and best practices for Generative AI development across teams.
- Guide the implementation of prompt engineering strategies, evaluation frameworks, and AI observability practices.
- Collaborate with architects, data engineers, and business stakeholders to identify and prioritize AI use cases.
- Evaluate emerging AI technologies, frameworks, and tools, recommending practical adoption strategies.
- Design integrations between AI platforms, enterprise systems, APIs, and data sources.
- Ensure AI solutions align with security, compliance, responsible AI, and data governance requirements.
- Mentor engineering teams on AI development patterns, framework selection, and implementation best practices.
- Drive the adoption of reusable AI accelerators, agent workflows, and scalable AI engineering patterns.
Requirements / Skills
- Bachelor's or Master's degree in Computer Science, Software Engineering, Information Technology, or a related field.
- 8-12 years of professional software engineering experience.
- Strong hands-on experience developing and delivering enterprise-scale applications using Python and/or Java.
- Proven experience designing distributed systems, APIs, microservices, and cloud-native architectures.
- Strong experience building modern web applications using React or similar front-end frameworks.
- Solid understanding of enterprise integration patterns, software architecture principles, and system design methodologies.
- Experience working with Microsoft Azure (preferred) and/or AWS cloud platforms.
- Strong experience with DevOps practices including CI/CD pipelines, containerization, Kubernetes, Infrastructure as Code, and deployment automation.
- Familiarity with Azure DevOps, GitHub Actions, Terraform, and modern software delivery practices.
- Experience working with relational databases, NoSQL databases, and enterprise data platforms.
- Strong analytical, troubleshooting, and problem-solving abilities.
- Excellent communication and stakeholder management skills with the ability to engage effectively with technical and non-technical audiences.
- Demonstrated experience mentoring engineers and leading technical initiatives.
Preferred AI Skills & Experience
- Hands-on experience designing and deploying Generative AI solutions in production environments.
- Strong understanding of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, and AI orchestration patterns.
- Experience working with frameworks such as LangChain, Semantic Kernel, LlamaIndex, AutoGen, CrewAI, or similar technologies.
- Experience integrating solutions using Azure OpenAI, Azure AI Foundry, AWS Bedrock, Anthropic, OpenAI APIs, or equivalent AI platforms.
- Experience with vector databases, embeddings, semantic search, knowledge retrieval systems, and AI evaluation frameworks.
- Understanding of prompt engineering, model evaluation, AI observability, and performance optimization techniques.
- Familiarity with emerging AI interoperability standards such as MCP (Model Context Protocol) and agent communication patterns.
- Experience building AI-enabled workflows, intelligent automation solutions, and enterprise AI integrations.
- Exposure to Snowflake, Databricks, modern data engineering platforms, and AI/ML infrastructure is highly desirable.
Your specific salary will be determined based on several factors:
Location-based market rate for the role
Your abilities in relation to the job specification
Performance during screening and interview
Pay parity with the wider team in the considered location
Further details about the package will be provided during the initial screening call with the Talent Acquisition Team.
Click here to learn about Epiq's Benefits.
Epiq Leadership Compass
Fosters Relationships & Collaboration
Builds trust and alignment through open communication, shared goals, and strong partnerships to drive collective success.
Build trust-based partnerships
Nurture long-term relationships
Remove collaboration barriers
Celebrate cross-team success
Engages & Influences
Inspires action and alignment through clear communication, purposeful influence, and a compelling vision.
Use storytelling to build buy-in
Align communication with organizational goals
Guild alignment through strong engagement
Maximizes Performance
Sets and reinforces performance standards that drive results, ensure accountability, and align with Epiq’s goals.
Use data to identify improvement opportunities
Make informed decisions
Align team goals with boarder strategy
Empower teams to manage their own goals
Translate vision into clear priorities
Prepare for disruptions with strong change management
Achieves Operational Success
Drives continuous improvement and operational excellence through smart processes, data insights, and quality execution.
Improve workflows for team efficiency
Use clear documentation and expectations
Resolve issues quickly using data and feedback
It is Epiq’s policy to comply with all applicable equal employment opportunity laws by making all employment decisions without unlawful regard or consideration of any individual’s race, religion, ethnicity, color, sex, sexual orientation, gender identity or expressions, transgender status, sexual and other reproductive health decisions, marital status, age, national origin, genetic information, ancestry, citizenship, physical or mental disability, veteran or family status or any other basis protected by applicable national, federal, state, provincial or local law. Epiq’s policy prohibits unlawful discrimination based on any of these impermissible bases, as well as any bases or grounds protected by applicable law in each jurisdiction. In addition Epiq will take affirmative action for minorities, women, covered veterans and individuals with disabilities. If you need assistance or an accommodation during the application process because of a disability, it is available upon request. Epiq is pleased to provide such assistance and no applicant will be penalized as a result of such a request. Pursuant to relevant law, where applicable, Epiq will consider for employment qualified applicants with arrest and conviction records.
