Job Title

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.