Postúlate en Kit Empleo: kitempleo.com.ar/empleo/qex5d

As a Senior AI/ML Engineer at the client, you will build the AI capabilities that power platforms across our client engagements.
You will own reusable AI skills shared across projects:
Document Intelligence pipelines, RAG over enterprise document libraries, GPT-4o reasoning chains for summarization and analysis, classification and field extraction with GPT-4o-mini, and agent orchestration.
You will partner with Technical Leads, data engineers, and backend engineers to build accurate, auditable, confidence-gated AI workflows for regulated workloads.
What qualifications make you a Senior AI/ML Engineer?
An AI engineer who designs for accuracy, auditability, and human oversight rather than impressive demos.
A clear communicator who can explain prompt design, RAG architecture, and accuracy trade-offs to engineers, architects, and client stakeholders.
Comfortable operating with ambiguity, capable of building skills in domains where the right answer requires domain expertise to validate.
A mentor who raises the bar through prompt review, evaluation design, and pattern guidance.
Customer-obsessed and outcome-focused, treating accuracy thresholds, HITL design, and audit trail as features that protect regulated work.
Responsibilities
AI Skills & Document Intelligence
Build reusable AI skills consumed across engagements: Document Intelligence, document summarization, data normalization, anomaly detection, matching engines, and compliance test runners.
Design and train custom Document Intelligence neural models for client-specific document types.
Reasoning, Agents & Evaluation
Build LLM reasoning chains using Azure OpenAI (GPT-4o for complex reasoning, GPT-4o-mini for high-volume classification) with prompt versioning and guardrails.
Design agent orchestration in Azure AI Foundry for multi-step workflows: extract, search, reason, and generate output with tool-use grounding.
Build evaluation harnesses, accuracy thresholds, and drift detection; tie outputs to confidence-gated HITL review tiers.
Production AI, Compliance & Mentorship




Implement audit trail patterns for AI-assisted workloads: prompt/response logging, evidence chains, and SOC 2 aligned event sourcing.
Operate AI Foundry deployments, manage PTU vs. token-based billing decisions, and monitor accuracy and cost in production.
Mentor engineers on prompt engineering, RAG design, agentic patterns, and evaluation; contribute to the client AI engineering standards.
Qualifications
Bachelor's Degree in Computer Science, Machine Learning, or a related discipline, or equivalent experience; MUST be proficient in written and spoken English (85%).
5 to 8 years of professional engineering experience with at least 3 years building production AI / ML systems.
Expert-level proficiency in Azure AI services, including Azure OpenAI (GPT-4o, GPT-4o-mini, PTU and token-based billing), Azure AI Foundry, Document Intelligence (custom neural models), and AI Search.
Expert-level proficiency in RAG and agent design, including hybrid retrieval, semantic ranking, prompt versioning, guardrails, evaluation harnesses, and confidence-aware HITL design.
Strong proficiency in Python for AI/ML development, including modern frameworks for LLM applications (LangChain, LangGraph, Semantic Kernel, or equivalent).
Hands-on experience with Document Intelligence custom models, including training, evaluation, and production deployment of neural extraction models.
Experience designing AI workflows for regulated environments: audit trail, prompt/response logging, accuracy thresholds, and drift detection.
Working knowledge of Medallion data architecture, vector databases, and embedding pipelines.
Solid Git, code review, and engineering standards discipline; experience with trunk-based development and IaC for AI deployments.
Experience in financial services, professional services, or other regulated industries is a plus.
Experience with .
NET interop or polyglot AI service ecosystems is a plus.
Excellent analytical and problem-solving skills; strong communication, collaboration, customer orientation, innovation mindset, and adaptability under ambiguity.
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Postúlate en Kit Empleo: kitempleo.com.ar/empleo/qex5d

📌 Senior Ai/Ml Engineer (Buenos Aires)
🏢 Techunting
📍 Buenos Aires