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Senior Backend Engineer
DeepSee.ai
Software Engineering
draper, ut, usa
Posted on Nov 4, 2025
Job Description
DeepSee delivers an open and flexible agentic platform to accelerate AI adoption for financial services in front, middle, and back-office operations. Our cloud-based platform seamlessly integrates with existing bank architectures, whether they’re just starting their AI transformation journey or looking to enhance existing in-house capabilities with Agentic AI solutions. With DeepSee’s pre-trained & pre-configured agents, banking and capital markets firms can automate and orchestrate manual, repetitive tasks—freeing domain experts for strategic work, reducing risk, and streamlining operations to drive greater efficiency.
We are looking for an experienced and forward-thinking Sr. Backend Engineer to to architect and build high-performance, scalable backend services as part of a best-in-class engineering organization. The role is ideal for someone who thrives in a polygot environment (Java & Python), can tackle complex performance challenges, and is working with and excited about cutting-edge AI technologies.
Job Responsibilities:
Backend Architecture & Performance
- Design and implement scalable microservices using Java (Spring Boot) and Python (FastAPI) in a modern cloud-native architecture
- Optimize high-throughput data processing pipelines handling large volumes of emails and documents
- Identify and resolve performance bottlenecks in CPU-intensive document extraction and processing workflows
Database & Data Engineering
- Design complex PostgreSQL queries and optimize database performance through strategic indexing and query refactoring
- Work with both relational (PostgreSQL) and NoSQL (e.g., MongoDB) databases to ensure efficient data persistence
- Implement robust data pipelines with event-driven architecture using Kafka
- Eliminate N+1 query patterns and implement efficient data access patterns
AI & Intelligent Automation
- Build and deploy production-ready agentic AI systems using frameworks (e.g., Semantic Kernel, LangChain, LangGraph, agent-framework, and SDKs)
- Integrate Azure OpenAI, Azure Foundry and other LLM services into backend processing workflows
- Implement guardrails, tracing, monitoring, and human-in-the-loop systems for AI agent operations
- Design intelligent document extraction and classification systems to enhance automation
- Use transfer learning, model distillation, and ensemble model techniques to create fit-for-purpose models that are highly performant and accurate
System Reliability & Observability
- Implement comprehensive monitoring, logging, and alerting using Prometheus, Grafana, and distributed tracing tools
- Establish SLO/SLI metrics and performance dashboards for production systems
- Design fault-tolerant systems with proper error handling, retry logic, and circuit breakers
- Write thorough unit, integration, and smoke tests using JUnit, Mockito, Pytest, and Playwright
Collaboration & Technical Leadership
- Work closely with Product and Engineering teams to translate requirements into technical solutions
- Conduct code reviews and mentor team members on best practices
- Document architectural decisions (ADRs) and create operational runbooks
- Deep dive technically while also operating at the strategic, organizational level
Core Backend Engineering
- 5+ years of backend development experience with strong fundamentals in distributed systems and microservices architecture
- Strong proficiency in Python 3.10+ including asynchronous programming, FastAPI, and async/await patterns
- Solid Java experience (Java 17+) with Spring Boot, Spring Data JPA, and RESTful API development
- Expert-level SQL skills with PostgreSQL, including complex query optimization and index design
- Event-driven architecture experience with Kafka or similar message queue systems
- Testing expertise with JUnit, Mockito, and Pytest for comprehensive test coverage
AI & Modern Development
- Production experience building and deploying agentic AI systems (LangChain, LangGraph, agent-framework, or similar)
- Strong understanding of LLM integration patterns, prompt engineering, and AI observability/tracing
- Experience with Docker containerization and cloud platforms (AWS/Azure)
- Proficiency with modern development tools: Git, uv, Gradle, pre-commit hooks, linting/formatting automation
Mindset & Approach
- Comfortable with ambiguity and rapid change in a fast-paced startup environment
- Strong problem-solving skills with ability to diagnose and resolve complex performance issues
- Ownership mentality—responsible for the reliability of systems you build, including on-call participation
- Ability to leverage AI tools (GitHub Copilot, Claude, ChatGPT) to augment productivity
Nice to Haves:
Advanced Technical Skills
- Experience with MapStruct for Java bean mapping and Tortoise ORM for async Python persistence
- Document processing libraries: Apache Tika, PDFBox, Apache POI for PDF, Excel, and email parsing
- Microsoft Graph API integration, especially for Outlook/email automation
- Knowledge graph design and development using open-source tools
- OpenAPI/Swagger for API documentation and contract-first development
- Feature flag systems for progressive rollouts and A/B testing
- Rust toolchain familiarity or HTTPX for high-performance HTTP operations
Domain Expertise
- Experience in financial services, banking, or capital markets with understanding of regulatory requirements (SOC2, ISO27001)
- Domain-Driven Design (DDD) principles and implementation patterns
- Background in ETL pipelines and data-intensive applications
- Exposure to Azure AI Foundry, Microsoft 365 Agents SDK, or Copilot integration
- Understanding of MCP (Model Context Protocol) and A2A (Agent-to-Agent) communication patterns
Personal Attributes
- Experience-driven empathy for engineering pain points—you've felt the frustration of poorly architected systems and know how to fix them
- A voracious and intrinsic desire to learn and fill in missing skills—and an equally strong talent for sharing learnings clearly and concisely with others
- Track record of successfully refactoring legacy codebases while maintaining system stability
Finally, it is important that you align with our Stuff That Matters.
Knowledge Over Noise: We prioritize actionable insights
One Team, One Dream: We collaborate seamlessly across functions
Be a Seeker: We constantly pursue innovation and learning
Stay Human: We keep our solutions people-centric
Act Boldly: We take calculated risks to drive progress
Believe: We’re passionate about our mission
Own It: We take responsibility for our work and its impact
Why DeepSee.ai?
Competitive compensation package including equity, with remote work options
100% company-paid premiums on health, dental, and vision insurance
Opportunity to work on cutting-edge AI technology with real impact
Collaborative and innovative work environment
Join us in shaping the future of AI-powered automation and make a significant impact in a rapidly growing startup. If you’re a hands-on problem solver who thrives in fast-paced environments and is excited about leveraging AI to solve complex problems, we want to hear from you!