Senior Developer – Generative AI

What we're working on:

At Lumenalta, we help global enterprises build and scale digital products powered by high-volume, high-impact data. Our work spans modern cloud data platforms, complex transformation pipelines, and real-time business insights.

Now, we’re extending that foundation with Generative AI—designing intelligent systems that not only process data but create with it. From LLM-powered automation to intelligent agents and AI-enhanced user experiences, our GenAI initiatives are pushing the boundaries of what enterprise data products can be. If you're passionate about applied AI, this is your chance to help shape the next generation of data-driven innovation at scale.

What You’ll Do

• Design, develop, and deploy applications powered by large language models (LLMs) and generative AI technologies (e.g., OpenAI, Claude, Mistral, open-source LLMs)
• Fine-tune models for domain-specific use cases using techniques like LoRA, RAG, prompt engineering, and embeddings
• Collaborate with cross-functional teams including product managers, researchers, and data engineers to build end-to-end GenAI features
• Build robust pipelines for model evaluation, data preprocessing, and deployment (e.g., LangChain, Pinecone, Weaviate, vector databases)
• Optimize inference performance, model cost, and safety guardrails
• Stay ahead of advancements in the GenAI ecosystem and guide adoption of emerging tools and techniques

What We’re Looking For

• 5+ years of experience in software engineering, with a strong track record of building scalable applications
• Proven experience working with LLMs, transformer architectures, or deploying GenAI features into production
• Proficiency in Python (TypeScript or Go is a plus)
• Hands-on experience with libraries and tools like LangChain, Hugging Face, OpenAI API, TensorFlow, or PyTorch
• Solid grasp of cloud services (AWS, GCP, or Azure), Docker, and CI/CD best practices
• Comfortable working in ambiguous problem spaces and fast-paced environments
• Bonus: Experience with vector databases, RAG architecture, prompt evaluation, or AI safety frameworks