2 months ago
Bengaluru, IndiaMid Level
Responsibilities
- Design, build, and deploy AI-powered features across Alaan’s products.
- Create workflows for prompt management, model orchestration, tool calling, and structured outputs.
- Build backend services and APIs that integrate AI capabilities into production applications.
- Develop evaluation frameworks for AI output accuracy, relevance, reliability, latency, and cost.
- Experiment with models, prompting techniques, embeddings, retrieval strategies, and fine-tuning approaches.
- Implement safeguards for sensitive financial and customer information.
- Monitor production AI systems and improve them using user feedback and evaluation data.
- Collaborate with Product Managers, Designers, Data teams, and Backend Engineers to identify high-impact AI use cases.
Requirements
- At least 2 years of software engineering experience with meaningful hands-on experience building AI- or machine-learning-powered applications.
- Strong programming skills in Python and Node.js for production AI applications and backend services.
- Hands-on experience with AWS SageMaker, Jupyter Notebooks, and Weights & Biases.
- Hands-on experience with large language models and their APIs, prompt engineering, embeddings, vector search, and RAG.
- Experience managing prompt versions and the complete lifecycle of business use cases.
- Experience with PostgreSQL, MongoDB, and at least one vector database or vector-search solution such as OpenSearch.
- Experience evaluating AI applications beyond manual testing or subjective output reviews.
- Familiarity with AWS, GCP, or Azure and understanding of testing, version control, observability, scalability, and security.
- Ability to translate loosely defined business problems into practical AI solutions and move between experimentation and production implementation.
- Preferred experience includes LangChain, PromptFoo, LangFuse, model evaluation and monitoring platforms, Snowflake, open-source model fine-tuning or serving, document intelligence, OCR, classification, recommendation systems, conversational AI, agent loops, and fintech or SaaS environments.
Benefits
- Flexible hybrid culture with work-life balance.
- Exciting offsite events.
- Competitive salary and equity.
- Travel allowances, gym memberships, and additional perks.
- Significant ownership and accountability while building a high-growth fintech platform.
Tech Stack
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