7 hours 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 integrating AI capabilities into production applications.
- Develop evaluation frameworks measuring 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 performance using user feedback and evaluation data.
- Collaborate with Product Managers, Designers, Data teams, and Backend Engineers to identify high-impact AI use cases.
- Determine which applied-AI technologies are useful for Alaan’s products.
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 for developing, training, deploying, and monitoring AI or machine-learning workloads.
- Proficiency with Jupyter Notebooks for data exploration, experimentation, model development, and prototyping.
- Hands-on experience with Weights & Biases for experiment tracking, model evaluation, versioning, and performance monitoring.
- Hands-on experience with large language models and their APIs.
- Practical understanding of prompt engineering, embeddings, vector search, and RAG.
- Experience managing prompt version control 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.
- Understanding of software engineering principles including testing, version control, observability, scalability, and security.
- Strong product judgment and ability to translate loosely defined business problems into practical AI solutions.
- Ability to move between experimentation and production-quality implementation.
- Preferred experience with LangChain, PromptFoo, LangFuse, or similar AI orchestration tools.
- Preferred experience with model evaluation, guardrails, observability, and monitoring platforms.
- Preferred experience with Snowflake or a similar data warehouse or lake.
- Preferred experience fine-tuning, adapting, or serving open-source models.
- Preferred experience with document intelligence, OCR, classification, recommendation systems, conversational AI, harnesses, and agent loops.
- Experience with financial, accounting, or other sensitive data and fintech, SaaS, or high-growth startup environments is preferred.
Benefits
- Flexible hybrid culture with ample work-life balance.
- Exciting offsite events.
- Competitive salary and equity.
- Travel allowances, gym memberships, and additional perks.
- Significant ownership and accountability while contributing to a growing fintech platform.
Tech Stack
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