Senior Software Engineer, AI Applications

Key Responsibilities AI Application Development

• Design, develop, and maintain production-grade AI-powered applications and services.
• Build and integrate solutions leveraging LLMs, generative AI platforms, vector databases, embeddings, and agent frameworks.
• Implement Retrieval-Augmented Generation (RAG) architectures and knowledge retrieval systems.
• Develop prompt engineering strategies, evaluation frameworks, and guardrails to improve AI quality and reliability.
• Integrate AI capabilities into existing products, workflows, and business processes.

Software Engineering & Architecture

• Design scalable, secure, and maintainable software systems using modern engineering practices.
• Develop APIs, microservices, and cloud-native applications supporting AI workloads.
• Create reusable frameworks and components that accelerate AI product development.
• Ensure solutions meet performance, reliability, observability, and security standards.
• Participate in architecture reviews and technical design discussions.

AI Operations & Model Management

• Evaluate, benchmark, and optimize AI models and providers for quality, latency, and cost.
• Implement monitoring, logging, testing, and observability for AI systems. Establish processes for model evaluation, prompt versioning, and continuous improvement.
• Collaborate with data and platform teams to manage AI infrastructure and deployment pipelines.

Collaboration & Leadership

• Partner with product management to identify and prioritize AI opportunities.
• Mentor engineers and contribute to team-wide technical growth.
• Drive engineering best practices, code quality, and architectural standards.
• Participate in code reviews and provide technical leadership on complex initiatives.
• Communicate technical concepts effectively to both technical and non-technical stakeholders.

Required Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, or related field, or equivalent practical experience.
• 5+ years of professional software engineering experience.
• 2+ years developing AI, machine learning, or generative AI applications.
• Strong proficiency in one or more modern programming languages such as Python, TypeScript, Java, or C#.
• Experience building and deploying cloud-native applications on AWS, Azure, or Google Cloud.
• Experience with coding harnesses
• Experience with RESTful APIs, distributed systems, and microservice architectures.
• Hands-on experience with LLMs and AI platforms such as OpenAI, Anthropic, Azure OpenAI, Google Gemini, or similar.
• Experience implementing RAG solutions, vector databases, and semantic search.
• Strong understanding of software development lifecycle, CI/CD, testing, and DevOps practices.
• Excellent problem-solving, communication, and collaboration skills.

Preferred Qualifications

• Experience with agentic AI frameworks such as Strands, LangChain, LangGraph, Semantic Kernel, CrewAI, or similar.
• Experience with vector databases such as Pinecone, Weaviate, Qdrant, Chroma, or Azure AI Search.
• Familiarity with MLOps and AI evaluation frameworks.
• Experience deploying AI workloads using Kubernetes and containerized environments.
• Knowledge of AI governance, security, compliance, and responsible AI practices.
• Experience in healthcare, fintech, SaaS, or other regulated industries.
• Contributions to open-source AI projects or technical communities.

Equal Opportunity Employer

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