Senior Software Engineer – AI Applications
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Job Description:
Position Summary
We are seeking a Senior Software Engineer – AI Applications. In this role, you will design, develop, and maintain cloud-native, AI-driven products for Epiq's Fortune-500 customers. This role requires strong development skills, a passion for AI-driven products, and an understanding of Cloud services.
This role is part of Epiq's Legal Solutions (LS) business and a team member of LS Hyderabad-based product-engineering teams of 75+ employees. This role is also the first hire of a new team chartered to build next-generation legal and compliance products.
Job Responsibilities
- Development: Design, develop, ship, and maintain applications using modern frameworks and technologies. Own roadmaps, plans, and timelines. Lead architectural discussions and make technical decisions. Work on both rapid prototypes and enterprise-quality, high-scale products.
- AI Applications: Select and deploy foundation models and LLMs as a service. Write and refine prompts. Measure, evaluate, and optimize model performance. Integrate models into workflows. Extend model capabilities with memory, tools, guardrails, and multi-agent patterns. Acquire, clean, and synthesize data sets. Partner with domain experts to capture knowledge. Stay current with AI trends and apply them to solve real-world problems.
- Cloud: Leverage the tools and services of a major cloud provider. Build APIs, microservices, and serverless functions to support application functionality. Manage our cloud environment and CI/CD pipelines. Make tradeoffs around performance and cost.
- Communications: Partner with business leaders in India, US, and Europe. Clearly communicate status, technical challenges, tradeoffs, and insights.
- Collaboration: Work closely with product managers, designers, data scientists, domain experts, and lead customers. Help shape requirements and roadmap. Help manage complex tradeoffs in speed, quality, and scope.
- Leadership: Build relationships, raise issues, define alternatives, and uncover resources. Establish practices, processes, and culture for a growing team.
- Education: Bachelor’s in Computer Science, Engineering, AI/ML, or a related field. Master’s preferred.
- Experience: 5+ years of experience as a software engineer, as an AI/ML/Data engineer, or in a similar role.
- Development: Proficient in Python or JavaScript/Typescript. Java/Go/C++ nice to have. Hands-on back-end experience. Familiarity with common front-end technologies. Familiarity with relational, non-relational and vector databases. Comfort with Agile processes.
- AI: More than one year of engineering experience (including relevant projects) building production-quality applications leveraging LLMs. Experience with frameworks for AI applications (e.g., LangChain, LlamaIndex, Haystack). Knowledge of deep learning and ML frameworks (e.g., TensorFlow, PyTorch). Experience managing data sets. Familiarity with MLOps.
- Cloud: Experience with cloud platforms (e.g., AWS, Azure, or GCP). Solid understanding of RESTful APIs, microservices architecture, and containerization.
- Soft skills: Excellent communications and collaboration skills. Results-driven, entrepreneurial, and comfortable working from 0→1.
- Physical Requirements: Ability to work in an office environment and perform tasks that may require sitting, standing, and using office equipment.
- 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
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
- Use storytelling to build buy-in
- Align communication with organizational goals
- Guild alignment through strong engagement
- 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
- Improve workflows for team efficiency
- Use clear documentation and expectations
- Resolve issues quickly using data and feedback
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