This position requires a bachelor’s degree in computer science, or a related field, or foreign equivalent and 5 years of relevant experience as a Software Engineer, Application Development Associate, or in a related position. In alternative, we accept a Master’s degree in Computer Science, or a related field, or foreign equivalent and 3 years of relevant experience as a Software Engineer, Application Development Associate, or in a related position.
This position also requires database engineering management through RDBMS (SQL Server, PostgreSQL) including design, normalization, optimization, sharding, ACID transactions, and migrations. Python Development: Production applications, APIs (calling and invoking, Rest API’s) for data preprocessing. Object-oriented programming in Python/Java, including OOP design patterns and UML architecture. Data processing and visualization by using QlikView and Python (Pandas, Plotly, Matplotlib). Agile development practices with emphasis on customer-centric delivery. Cloud and infrastructure management by using various cloud services such as AWS S3, Aurora, RDS, API Gateway, and AWS Lambda. Machine learning and statistical methods, including natural language processing (NLP) and embeddings. Version control and CI/CD (Git, application deployment and monitoring tools). Authoring technical documentation for developers, technical, and non-technical users. Vector Databases & Retrieval: Weaviate, Pinecone, GraphQL-based querying, AI-powered retrieval. Scalability & Performance: Queuebased request handling (SQS, Celery), event-driven architectures, caching using in-memory data structures such as Redis. AI Adoption: Driving AI tool adoption within enterprises. Multiprovider integration (OpenAI, Anthropic, MistralAI, etc.), Retrieval augmented generation, function calling, structured outputs, conversational memory. Prompt Engineering: Chain-ofthought prompting, prompt caching, zero-shot prompting. Agentic Frameworks: LangGraph or AutoGen for building agentic orchestrations. Feature Flagging tools such as Split or CloudBees. Financial AI Applications: Investment-related AI, financial data analysis. Contributions to Python open-source projects or packages. LLM Understanding & Safety: Transformers, attention mechanisms, fine-tuning, hallucination mitigation, AI safety guardrails. **Will accept any suitable combination of education, training, and experience.