Codvo.ai - AI/ML Engineer

Description : AI/ML Engineer

Location : Work From Home

Employment Type : Full-Time

Experience Level : Mid-Level (3+ years)

Shift Timing : 9 : 30 AM 6 : 30 PM IST

Role Overview :

We're seeking an experienced AI/ML Engineer to design and implement intelligent exception resolution capabilities within our financial reconciliation platform.

You'll integrate advanced language models (Claude/OpenAI) into our core pipeline, crafting sophisticated prompts that transform complex reconciliation exceptions into clear, auditable resolution suggestions.

This role is critical to delivering AI-powered insights that help financial teams resolve discrepancies faster and with greater confidence.

What You'll Do :

- Design and optimize prompts that accurately interpret flagged reconciliation exceptions and generate structured, actionable resolution suggestions with confidence scoring.

- Integrate LLM APIs (Anthropic Claude, OpenAI) into the exception resolution layer using Python, the Anthropic SDK, and async API patterns for production-grade reliability.

- Develop human-in-the-loop workflows that balance automation with human oversight, ensuring financial accuracy and auditability at every step.

- Build robust API integration code that handles edge cases, rate limiting, token management, and graceful error recovery in a financial context.

- Collaborate with backend developers to embed AI outputs cleanly into the reconciliation pipeline and ensure seamless data flow into final reports.

- Implement LLM evaluation and benchmarking frameworks to measure prompt effectiveness, accuracy, and consistency across diverse exception types.

- Document prompt strategies and model behavior to enable knowledge sharing and continuous improvement across the engineering team.

- Monitor and iterate on model performance, refining prompts and integration logic based on real-world exception data and user feedback.

What We're Looking For :

Required Qualifications :

- 3+ years of professional software engineering experience, with at least 2+ years working directly with LLM APIs (Anthropic, OpenAI, or similar).

- Strong proficiency in Python, including hands-on experience with the Anthropic SDK and async API calls.

- Demonstrated expertise in prompt engineering, particularly for structured outputs and domain-specific tasks.

- Solid understanding of confidence scoring, uncertainty quantification, and human-in-the-loop AI workflows.

- Experience writing clean, maintainable API integration code with attention to edge cases and error handling.

- Ability to work independently and communicate effectively with cross-functional teams.

- Familiarity with financial systems, reconciliation processes, or similar regulated domains is a plus.

Technical Skills :

- Backend development and ETL middleware concepts.

- Agent orchestration and agentic AI patterns.

- LLM evaluation and benchmarking methodologies.

- Version control (Git) and collaborative development practices.

Nice to Have :

- Experience with Retrieval-Augmented Generation (RAG) or domain-specific knowledge grounding.

- Familiarity with financial reconciliation, accounting systems, or fintech platforms.

- Experience with prompt versioning and A/B testing frameworks.

- Knowledge of structured output formats (JSON, XML) and validation.

- Exposure to observability and monitoring tools for LLM applications.

- Background in machine learning model evaluation and metrics.

What We Offer :

- Flexible work environment : 100% remote with a collaborative, inclusive team culture.

- Meaningful impact : Work on cutting-edge AI solutions that directly improve financial operations for our clients.

- Professional growth : Opportunities to deepen expertise in LLMs, agentic AI, and financial technology.

- Competitive compensation : Commensurate with experience and market rates.

- Collaborative culture : Work alongside talented engineers and product teams who value innovation and continuous learning.

- Billable engagement : Full-time, stable project with mid-to-late stage engagement timeline.