We are seeking a Software Engineer with 5+ years of experience to help design and build AI-driven automation solutions for internal customer engagement and onboarding into enterprise cryptographic services.
This role focuses on developing Python-based, cloud-native applications that leverage natural language processing, GenAI/LLMs, and agentic workflows to automate manual analysis, understand customer intent, and guide users to the appropriate cryptographic services.
The ideal candidate has hands-on experience with AWS, modern AI/ML architectures, and containerized microservices, and enjoys working on end-to-end systems spanning data ingestion, AI orchestration, and secure cloud infrastructure.
Key Responsibilities
- Design and develop Python-based applications and services to automate internal customer engagement and onboarding workflows.
- Implement GenAI solutions using LLMs, embeddings, vector databases, and retrieval-augmented generation (RAG) architectures.
- Build NLP-enabled agents that can understand natural-language requests and assist users in selecting the appropriate cryptographic services.
- Automate manual analysis and triage processes using AI/ML and rule-based logic.
- Develop and maintain cloud-native microservices using AWS services such as Lambda, ECS/EKS, S3, DynamoDB, API Gateway, and Bedrock.
- Build and manage knowledge bases, embedding pipelines, and contextual retrieval systems for accurate, reliable responses.
- Design agentic workflows and orchestration logic to support decision-making and process automation.
- Collaborate with product, data, and engineering teams to translate business and compliance requirements into technical solutions.
- Monitor, troubleshoot, and optimize production workloads for performance, reliability, and cost efficiency.
Required Skills & Experience
- 5+ years of professional experience in software engineering, cloud engineering, or AI/ML development.
- Strong proficiency in Python (experience with FastAPI, Flask, or similar frameworks preferred).
- Hands-on experience with AWS cloud services, especially serverless and container-based architectures.
- Experience with Docker, GitHub, and CI/CD automation.
- Working knowledge of LLMs, prompt engineering, embeddings, and GenAI concepts.
- Experience building or contributing to RAG pipelines or search/knowledge-based AI systems.
- Familiarity with vector databases (e.g., Pinecone, FAISS, Redis, OpenSearch, or similar).
- Exposure to agentic frameworks (e.g., LangChain, LlamaIndex, or custom agent implementations).
- Understanding of API development, distributed systems, and cloud-native design patterns.
- Experience integrating with AWS Bedrock or other foundation model platforms.
- Exposure to security-focused or regulated environments (financial services, cryptography, compliance).
- Familiarity with infrastructure-as-code tools such as CloudFormation or CDK.
- Experience working on internal enterprise platforms rather than consumer applications.