Senior Software Engineer, Full Stack - AI

Senior Software Engineer, Full Stack - AI

We are seeking a Full Stack Software Engineer to design, build, and scale AI-enabled products that integrate Large Language Models (LLMs) into core business workflows. This role is focused on end-to-end product development-from frontend experiences to backend services and AI integrations-delivering secure, scalable, and production-grade solutions.You will work closely with Product, Design, Platform, and Data/AI partners to turn complex requirements into reliable, high-impact software.

What We Offer:

· Opportunity to work on AI-first product development, embedding LLM capabilities into real-world applications

· Ownership of full-stack delivery in a modern, cloud-native engineering environment

· Collaboration with senior engineers, architects, and AI platform teams

· Exposure to internal AI platforms, agentic frameworks, and GenAI enablement initiatives

· Strong engineering culture emphasizing design quality, scalability, and operational excellence

 

We’ll Count on You To:

Full Stack Product Development

• Design, develop, and maintain end-to-end web applications, including frontend UI, backend services, and data layers
• Build scalable, well-structured APIs and service integrations
• Translate product and business requirements into high-quality technical solutions
• Contribute to system design discussions and architectural decisions

• Build reusable data transformation logic using SQL and Python, and partner with analytics and product teams to deliver business‑ready datasets.

• Own features through the full development lifecycle: design → build → deploy → operate

AI / LLM Feature Engineering

• Develop and integrate LLM-powered capabilities such as chat interfaces, content generation, summarization, or decision support
• Implement retrieval-augmented generation (RAG) and context management patterns where applicable
• Work with internal AI platforms or approved LLM APIs to ensure consistency and compliance
• Optimize LLM usage for latency, cost, and quality tradeoffs
• Collaborate with AI platform teams on model integration patterns and best practices

Cloud & Platform Engineering

• Deploy and operate services in cloud environments using modern DevOps practices
• Implement observability (logging, metrics, tracing) to ensure production reliability
• Improve performance, scalability, and resilience of existing systems
• Participate in incident resolution and root-cause analysis for production issues

Secure & Governed Development

• Build AI-enabled features that comply with internal security, data handling, and AI governance standards
• Contribute required technical documentation for AI-enabled systems
• Ensure responsible use of LLMs, especially when handling proprietary or sensitive data

What You Need to Have:

• 7+ years of experience designing and developing distributed application architecture of moderate-to-high complexity.
• 3+ years in software engineering or applied ML building real-world AI/ML systems; strong Python proficiency and backend development expertise
• Hands-on experience building GenAI apps with LangChain and LangGraph, including agent design, state/memory management, and graph-based orchestration.
• Proficiency in ML/NLP and generative models; experience with embeddings, vector stores, RAG, and LLM integration/fine-tuning (OpenAI, LLaMA, Cohere, etc.)
• Strong coding in Python and experience with frameworks/tools such as FastAPI, PyTorch/TensorFlow, MLflow;
• 3-5+ years of experience in designing and developing scalable web applications using modern front-end frameworks such as React/TypeScript.
• Hands‑on experience with modern data platforms and cloud environments (e.g., Snowflake, Databricks, AWS and/or Azure).
• Experience building and operating data pipelines, including batch and streaming patterns, with orchestration tools such as Airflow, ADF, or Dagster.
• Experience working in high-performance teams using Agile methodologi