Job Title: AI/ML Engineer – Python & Agentic AI Systems
Location: Remote
Employment Type: Full-time
Experience: 5+ years of hands-on experience in backend engineering, AI/ML systems, or platform development, with demonstrated leadership in designing and scaling complex systems.
About the Role
We are seeking an AI/ML Engineer to design, build, and scale intelligent AI-driven systems using Python, RESTful APIs, and AWS AI/ML services. This role requires strong expertise in LLMs, agentic workflows, and document extraction systems, along with the ability to make informed architectural decisions by evaluating trade-offs across performance, cost, accuracy, and scalability.
The ideal candidate is hands-on, technically deep, and capable of guiding design discussions, reviewing complex codebases, and mentoring engineers while delivering production-grade AI solutions.
Key Responsibilities
Design and develop scalable, high-performance Python services
Build and maintain REST APIs using Python
Implement async processing for I/O-heavy and compute-intensive workloads
Design and implement LLM-based and agentic workflows using AWS AI services (such as Amazon Bedrock and SageMaker)
Architect document and data extraction pipelines for structured and unstructured inputs (PDFs and other formats)
Evaluate and clearly communicate technical trade-offs and architectural decisions
Debug, optimize, and harden systems for production environments
Review and refactor complex Python codebases, ensuring maintainability and type safety
Collaborate with cross-functional teams to translate business needs into scalable technical solutions
Required Skills & Experience
Strong hands-on Python development with production-grade coding practices
Experience building and maintaining APIs using python
Ability to write scalable async code using asyncio / async I/O patterns
Strong focus on type safety using typing and Pydantic (or equivalent)
Ability to read, understand, and refactor complex Python codebases
Hands-on exposure to AWS AI/ML services such as Amazon Bedrock, SageMaker, or AWS AI Builder tools
Experience with Amazon Textract or similar document AI services
Deep understanding of LLMs (context limits, latency, cost, hallucinations, evaluation)
Experience creating agents and agentic workflows (tool-calling, orchestration, multi-step flows)
Strong experience designing document extraction systems (PDFs and other unstructured formats → structured output)
Understanding of PDF extraction approaches and limitations (scanned vs digital, tables, layouts, OCR constraints)
Strong ability to discuss and justify trade-offs (accuracy vs latency, cost vs capability, OCR vs LLM, etc.)
Strong debugging and performance optimization skills across Python and ML/LLM stacks
Familiarity with logging, monitoring, and troubleshooting production issues in service-based systems on AWS
Soft Skills
Strong problem-solving and analytical thinking
Ability to clearly explain design decisions and trade-offs
Ownership mindset with a focus on quality and reliability
Effective communication with both technical and non-technical stakeholders
Mentorship and technical leadership capabilities
Comfort working in ambiguous, fast-evolving AI problem spaces
Nice-to-Have
Experience with multi-agent architectures
Exposure to evaluation frameworks for LLM outputs
Knowledge of cost optimization strategies for AI systems
Familiarity with cloud-native architectures on AWS
Experience working with large, enterprise-scale document workflows
Education
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
Equivalent practical experience will be considered in place of formal education.
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