ML/AI Engineer – Applied AI | Tech Solutions.ae | San Francisco or New York City, USA

Tech Solutions.ae; San Francisco, New York (CA, NY); On-site; USD 180,000 - 275,000; Full time

Job summary

Tech Solutions.ae is seeking an ML/AI Engineer – Applied AI to join a leading client in San Francisco or New York City. You will own production-grade AI systems, build retrieval pipelines, and collaborate with cross-functional teams to deliver enterprise-scale solutions.

You will work with hosted frontier AI models (OpenAI, Anthropic, Google Gemini, Cohere), develop robust evaluation methods, and ensure reliability, latency, and cost efficiency in production environments.

Qualifications

• 4–10 years of production ML or Applied AI experience.
• Strong hands-on with LLMs, embeddings, and prompt engineering.
• Experience designing evaluation frameworks and scalable services.

Responsibilities

• Design, develop, and deploy production-grade AI/ML systems.
• Build retrieval-augmented generation pipelines and contextual retrieval.
• Create robust evaluation datasets and quality gates.
• Develop structured data extraction and orchestration workflows.
• Monitor latency, reliability, and cost in production environments.

Skills

LLMs & prompt engineering

Python development

Production ML systems

Retrieval pipelines

Embeddings & vector DBs

Evaluation frameworks

Observability & reliability

Cross-functional collaboration

System design

Onsite work readiness

Education

Bachelor’s degree in CS or related

Tools

Python

Go

OpenAI API

Cohere

Job description

Job Title: ML/AI Engineer – Applied AI | Tech Solutions.ae | San Francisco or New York City, USA

Recruiting Company: Tech Solutions.ae

Job Location: San Francisco, California, USA or New York City, New York, USA

Job Type: Full-Time | Permanent | Onsite

Experience Required: 4-10 Years

Compensation: USD $180,000 – $275,000 per annum

Eligibility: Candidates currently based in San Francisco or New York City are strongly preferred.

Position Summary

Tech Solutions.ae is seeking a skilled ML/AI Engineer – Applied AI to join a leading client and help build enterprise-grade AI systems powered by cutting-edge large language models. This role focuses on transforming complex business data into actionable intelligence while delivering reliable, scalable, and production-ready AI solutions that directly impact customer workflows and operational efficiency.

Detailed Job Description

As an ML/AI Engineer specializing in Applied AI, you will own the full AI systems lifecycle, including retrieval pipelines, context engineering, model orchestration, structured data extraction, evaluation frameworks, and monitoring. You will work with hosted frontier AI models such as OpenAI, Anthropic, Google Gemini, and Cohere to build intelligent solutions for real-world enterprise challenges. The role requires close collaboration with product managers, backend engineers, and customer-facing technical teams to design and deploy high-quality AI applications. You will be responsible for developing robust evaluation methodologies, maintaining production reliability, and continuously improving model performance through testing and quality assurance processes. This is an excellent opportunity for engineers who enjoy combining machine learning, software engineering, and systems design to deliver measurable business outcomes.

Key Responsibilities

• Design, develop, and deploy production-grade AI and machine learning systems leveraging modern LLM technologies.
• Build retrieval-augmented generation (RAG) pipelines using embeddings, vector databases, reranking, and contextual retrieval techniques.
• Create robust evaluation datasets, testing frameworks, and quality gates to measure model performance and prevent regressions.
• Implement structured extraction pipelines that convert unstructured enterprise data into actionable business intelligence.
• Develop orchestration workflows that coordinate AI models, tools, and external services within complex applications.
• Monitor and optimize production workloads for latency, reliability, scalability, cost efficiency, and observability.
• Collaborate with backend, product, and forward-deployed engineering teams to solve customer workflow challenges.
• Build data pipelines and services using Python and modern software engineering best practices.
• Evaluate and select appropriate AI models, providers, and architecture based on performance and business requirements.
• Support continuous improvement initiatives through experimentation, testing, and performance analysis.

Required Qualifications & Skills

• Bachelor’s degree or higher in Computer Science, Software Engineering, Artificial Intelligence, Machine Learning, or a related technical discipline.
• 4-10 years of experience building and operating production ML or Applied AI systems.
• Strong hands-on experience with Large Language Models (LLMs), prompt engineering, structured outputs, embeddings, retrieval systems, and tool integration.
• Advanced Python development skills with experience building scalable services and automated data workflows.
• Proven experience designing evaluation frameworks, testing methodologies, and quality measurement systems.
• Strong understanding of production AI operations, including observability, latency optimization, reliability, and cost management.
• Experience designing end-to-end data and AI pipelines from raw data ingestion to business-ready outputs.
• Excellent analytical, problem-solving, and systems-thinking capabilities.
• Ability to work effectively within cross-functional engineering and product teams.
• Availability to work onsite in either San Francisco or New York City.

Nice-to-Have Skills

• Hands-on experience with Retrieval-Augmented Generation (RAG) architectures and vector search platforms.
• Expertise in LLM evaluation methodologies including golden datasets, regression testing, and LLM-as-a-judge approaches.
• Experience with agentic AI systems, tool calling, and multi-step workflow orchestration.
• Knowledge of multimodal AI systems involving documents, screenshots, video, audio, and transcription workflows.
• Experience developing backend services using Go and modern distributed architectures.
• Exposure to process mining, business process automation, or enterprise workflow intelligence platforms.

Recruitment Pro Tip

To stand out for this role, showcase specific AI systems you have deployed into production, including measurable outcomes such as accuracy improvements, latency reductions, cost savings, or user adoption metrics. Demonstrating hands-on experience with RAG architectures, LLM evaluations, and enterprise-scale AI deployments will significantly strengthen your application.