Senior Ai Engineer

About This Opportunity

We are representing a confidential SaaS organization seeking a Senior AI Engineer to join their growing AI Engineering team. This is a remote position offering the chance to build production AI systems that power conversational data collection experiences used by thousands of businesses worldwide.

Our client is investing heavily in generative AI, RAG systems, and agentic workflows. As a Senior AI Engineer, you'll own the full journey from experimentation to production deployment, working across AI application development, evaluation frameworks, infrastructure, and observability.

Responsibilities

Build and deliver AI products

• Design, build, and deploy generative AI capabilities across product offerings
• Develop applications using large language models, RAG, vector search, and agentic systems
• Build services and APIs that allow product teams to integrate AI capabilities into customer experiences
• Turn prototypes into reliable production systems with clear measures of performance and quality
• Explore new ways for customers to collect, understand, and act on information using AI

Build scalable AI systems

• Design and operate machine learning services and workflows using Python, Docker, Kubernetes, and AWS
• Build reliable pipelines for batch and real-time processing using technologies such as Kafka and Airflow
• Design solutions using vector databases to support retrieval, recommendations, personalization, and semantic search
• Use MLflow to manage experiments, model versions, registries, and deployments
• Improve the reliability, performance, scalability, and cost efficiency of AI systems

Evaluate and improve AI quality

• Build automated evaluation pipelines for generative AI applications
• Develop benchmarks that measure accuracy, relevance, reliability, fairness, latency, and cost
• Evaluate retrieval strategies, including chunking, embeddings, context selection, and reranking
• Monitor AI systems in production and identify opportunities to improve quality and performance
• Create safeguards that reduce unexpected behavior and protect customer data

Shape AI engineering practice

• Establish reusable patterns and technical standards for building, evaluating, and releasing AI systems
• Help teams make informed decisions about models, frameworks, infrastructure, performance, and cost
• Apply strong engineering practices across testing, security, observability, version control, and deployment
• Share technical knowledge and support the development of other engineers
• Keep current with relevant AI research, tools, and engineering practices

Collaborate across teams

• Partner with Product, Engineering, Data Science, Data Engineering, and Analytics teams
• Work with Data Scientists to turn experiments and models into reliable production services
• Communicate technical concepts, risks, and tradeoffs clearly to technical and non-technical partners
• Contribute to technical planning and help shape AI direction

What We're Looking For

Required qualifications:

• At least four years of experience building and deploying machine learning or AI systems in production
• Strong Python and software engineering skills
• Experience building production services using Python frameworks such as FastAPI
• Practical experience developing generative AI applications using large language models, RAG, tool use, or agentic systems
• Experience with frameworks such as PyTorch, LangChain, LangGraph, or similar technologies
• Strong understanding of enterprise RAG systems, including chunking, embeddings, retrieval, reranking, evaluation, and monitoring
• Experience creating automated evaluations for generative AI applications
• Experience with AWS, Docker, Kubernetes, Terraform, and CI/CD practices
• Experience using services such as AWS SageMaker or AWS Bedrock
• Experience with Kafka, vector databases, or other technologies for real-time and high-dimensional data processing
• Experience managing machine learning workflows using MLflow
• Experience monitoring production systems with tools such as Datadog or OpenSearch
• Ability to balance quality, speed, reliability, scalability, and cost when making technical decisions
• Strong communication skills and experience collaborating with Product, Engineering, and Data teams

Preferred qualifications:

• Experience working in a B2B SaaS product company
• Experience with orchestration tools such as Airflow or Argo Workflows
• Familiarity with SQL, Spark, Snowflake, or other data processing technologies
• Experience building systems that combine structured data, unstructured data, and generative AI
• Experience with AI security, privacy, responsible AI, prompt injection protection, or data leakage prevention
• Experience improving the latency and cost of AI systems operating at scale

How We Work With You

When you apply through Get A Job.ai, our talent team will review your profile and arrange an initial screening conversation. If there's a strong match, we'll submit your candidacy to our client and guide you through their interview process. Please do not contact the client directly—all communication will flow through Get A Job.ai to ensure the best experience for everyone involved.

Pay

Compensation details will be discussed during the screening process based on experience and location.

Equal Opportunity

Get A Job.ai is committed to inclusive hiring practices. We welcome candidates of all backgrounds and do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity, or any other protected characteristic.