AI Engineer - DS&ML

CINTER CAREER USA, LLC

United States

8 days ago

Apply on www.indeed.com

Prepare application

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

5 years minimum

Working hours

Regular working hours

Job source

www.indeed.com

Tech stack

LangGraph Framework Clean Code Principles AI Evaluation Application Programming Interfaces (APIs) Agile Methodology Artificial Intelligence Amazon Web Services Automated Storage and Retrieval Systems Audit Trail Microsoft Azure Software Documentation Code Review

+32 more

Continuous Integration Data Governance Python (Programming Language) Knowledge Management Machine Learning Scrum Methodology Software Product Management OpenAI Search Technologies Software Engineering Systems Integration Workflow Management Systems LangChain Retrieval-Augmented Generation Large Language Models Multi-Agent Systems Prompt Engineering Model Validation Llamaindex Generative AI Agentic-AI AI Platforms Information Technology CrewAI AutoGen Machine Learning Operations Virtual Agents Evaluation of Large Language Models Google Gemini Semantic Kernel Automation Anywhere Human in the Loop

Job description

Design, build, evaluate, and operationalize enterprise-grade AI and Generative AI solutions supporting the DS/ML AI Accelerator.
Partner with data owners and business stakeholders to onboard approved documents, knowledge assets, and data sources into governed AI knowledge repositories.
Develop Retrieval-Augmented Generation (RAG) pipelines, metadata strategies, tagging frameworks, retrieval mechanisms, and source citation capabilities.
Create evaluation datasets and retrieval quality metrics to assess relevance, grounding, accuracy, and completeness of AI-generated outputs.
Ensure generated content clearly distinguishes factual information, assumptions, inferences, and areas requiring SME validation.
Design and implement secure multi-agent AI workflows leveraging LLMs, retrieval systems, APIs, and deterministic processes.
Define agent roles, workflow orchestration, tool integrations, validation rules, error handling, and human-in-the-loop review processes.
Develop reusable prompts, workflow patterns, and orchestration frameworks to improve scalability, governance, and user adoption.
Establish technical and business-oriented AI evaluation metrics, including correctness, traceability, latency, user effort, and operational cost.
Participate in Agile development processes, sprint planning, backlog refinement, and solution demonstrations.
Implement Responsible AI, security, privacy, data governance, and enterprise compliance requirements.
Create maintainable code, operational documentation, monitoring strategies, and knowledge refresh processes for long-term sustainability.
︎ The Right Candidate Will Possess

Requirements

Strong hands-on experience developing and deploying LLM-enabled applications in production environments.
Deep understanding of RAG architectures, embeddings, vector databases, search technologies, and knowledge management.
Experience designing AI agent workflows and orchestrating tools, workflows, and APIs.
Strong software engineering background with modern development best practices and collaborative delivery models.
Ability to transform ambiguous business requirements into measurable and scalable AI solutions.
Strong analytical mindset with the ability to evaluate AI quality, reliability, and business value.
Excellent communication skills and ability to collaborate effectively with technical and non-technical stakeholders.
Commitment to responsible AI, governance, security, privacy, and compliance standards.
︎ Required Qualifications & Skills
Bachelor’s degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, or a related field, or equivalent practical experience.
5+ years of experience in Software Engineering, Machine Learning Engineering, Data Science, AI Engineering, or related technical disciplines.
Hands-on experience building LLM-powered applications, AI assistants, RAG solutions, or agentic AI systems.
Strong Python development experience with production-quality coding practices.
Experience with APIs, structured tool integrations, testing frameworks, code reviews, CI/CD, observability, and software documentation.
Knowledge of embeddings, vector databases, semantic search, retrieval systems, and AI evaluation methodologies.
Experience defining and measuring AI quality metrics, retrieval effectiveness, and user outcomes.
Ability to communicate technical concepts and tradeoffs to both business and technical stakeholders.
Experience working within security, privacy, governance, and Responsible AI frameworks.
Experience working in Agile development environments and delivering solutions in iterative sprint cycles.
︎ Preferred Qualifications
Experience with AI orchestration and agent frameworks such as LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI, Semantic Kernel, or similar platforms.
Experience implementing LLM evaluation frameworks, guardrails, prompt management, telemetry, and model risk controls.
Experience supporting ML lifecycle management, model development, feature documentation, and AI product delivery.
Knowledge of enterprise data governance, auditability, access controls, and human-in-the-loop validation processes.
Experience working with Azure OpenAI, OpenAI, Anthropic, Gemini, AWS AI, or comparable enterprise AI platforms.
Experience deploying AI solutions within regulated or large enterprise environments.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.indeed.com

Prepare application

Good distractions

Loading talks and stories from around this role…