Senior Software Engineer, AI Products
Summary
The Senior Software Engineer will integrate LLMs and machine learning solutions into the company's platform, focusing on building AI-driven features, internal automation tools, and scalable ML infrastructure. The role requires strong expertise in Python, RAG pipelines, and production-level AI model deployment.
The role
As an AI Engineer, you will play a pivotal role in integrating large language models (LLMs) and machine learning (ML) solutions into our platform and internal systems. Your work will directly impact customer experiences, operational efficiency, and product innovation.
What You Will Be Doing:
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Build & Ship AI Based Features – Design, implement, and optimize AI-driven features for the platform, enhancing customer experience and business impact.
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AI-Powered Automation & Tooling – Develop LLM-based internal automation tools to streamline workflows, reduce manual effort, and improve team productivity.
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Scalable AI Infrastructure – Build and maintain a ML/LLM pipeline, ensuring robust, efficient, and scalable deployments.
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Performance & Cost Optimization – Improve AI model performance, balancing speed, quality, and infrastructure costs.
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Cross-Functional Collaboration – Work with product, engineering, and data teams to define AI/LLM use cases and share best practices.
What We’re Looking For:
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5+ years of technical experience: 5+ years of experience as a Backend Software engineer working directly with ML and Gen-AI or similar. Prior startup experience is preferred but not required.
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Strong LLM & ML Expertise: Experience working with LLM technologies (AWS Bedrock, OpenAI, Anthropic, Hugging Face models, or Llama etc.) in production and proficiency with prompt engineering, model selection, and ML/AI observability.
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Technology Skills: Proficiency in Python, vector databases (FAISS, Pinecone, Weaviate), and retrieval-augmented generation (RAG) pipelines. Experience with Django, AWS/GCP, and pytest preferred but not required.
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MLOps Experience: Familiarity with AI model deployment, monitoring, and scaling in production environments.
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Problem-Solving Mindset: Ability to tackle ambiguous AI challenges and develop scalable, efficient AI solutions.
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Collaboration & Communication: Comfortable working with engineers, data scientists, and product teams to define and implement AI-driven features.
Our Tech Stack:
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Infra: AWS, Fargate, Redis, PostgreSQL, SQS, CDK, Github, retool
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Backend: Django REST framework, Celery
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Frontend: Next.js, Tailwind css
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LLM: AWS Bedrock, OpenAI, Claude