Mid Level Software Engineer, Full Stack and Generative AI

• Design and develop scalable full stack applications with Angular frontends and microservices-based backends
• Build performant, secure RESTful and GraphQL APIs using modern backend frameworks (Java/Spring Boot, Python/FastAPI)
• Develop responsive, accessible frontends using Angular and TypeScript
• Collaborate with data engineers, security teams, and business analysts to translate regulatory requirements into technical solutions
• Responsibly adopt and leverage AI-assisted development tools while maintaining code quality standards and information security hygiene

Generative AI Integration

• Implement Generative AI solutions including LLM integration, prompt engineering, and RAG (Retrieval-Augmented Generation) pipelines
• Collaborate with data science teams to integrate ML models and implement model serving infrastructure
• Ensure responsible AI practices including human oversight and bias monitoring

CI/CD & Infrastructure

• Design and maintain CI/CD pipelines using tools such as Jenkins
• Implement infrastructure-as-code and containerized deployments (Docker, Kubernetes)
• Integrate automated testing (unit, integration, E2E) and security principles into delivery pipelines

Technical Leadership

• Provide technical guidance and mentorship to junior engineers through code reviews and pair programming
• Lead code reviews, establish best practices, and contribute to architectural decisions
• Ensure all systems meet technology compliance, audit, cybersecurity, and data governance standards

• Bachelor's degree in Computer Science, Software Engineering, or related field
• 5-7 years of professional software engineering experience
• Strong proficiency in backend languages: Python and/or Java
• 3+ years of production experience with Angular (latest versions), TypeScript, RxJS, and state management (NgRx)
• Experience designing and implementing RESTful APIs and/or GraphQL services
• Hands-on experience with AWS services (Lambda, ECS/EKS, API Gateway, S3, RDS, DynamoDB) and containerization (Docker, Kubernetes)
• Proficiency with both relational (PostgreSQL) and NoSQL (MongoDB, DynamoDB) databases
• Solid understanding of application security principles (OWASP Top 10, secrets management, least-privilege access)
• 1+ years working with LLMs (OpenAI, Anthropic, AWS Bedrock), prompt engineering, or embedding models

• Experience in regulatory or financial services environment
• Experience building human-in-the-loop review systems, annotation platforms, or approval workflows for AI outputs
• Experience with LangChain, LlamaIndex, or similar LLM orchestration frameworks
• Background implementing RAG architectures with vector databases (Pinecone, Weaviate, pgvector, OpenSearch)
• Familiarity with event-driven architectures and messaging systems (Kafka, AWS SQS/SNS, Kinesis)
• Exposure to observability tooling (Datadog, Grafana, CloudWatch) including AI/ML model monitoring
• Experience with microservices patterns (circuit breakers, service mesh, distributed tracing)
• Experience with feature flagging, canary deployments, or progressive delivery strategies
• Contributions to open-source projects or technical publications in AI/ML domains

• End-to-end ownership of features from UI to database
• Strong debugging and troubleshooting skills across the full technology stack
• Ability to balance business needs, technical constraints, and scalability
• Excellent collaboration and communication skills with cross-functional teams
• Strong commitment to automated testing and code quality
• Rapid adoption of new technologies, particularly in AI/ML landscape