Senior Gen AI Engineer

Fractal; Massachusetts; In loco; USD 120.000 - 150.000; Tempo pieno

Vantaggi offerti da questo lavoro

401(k) Plan

Paid Holidays (11)

Parental Leave (12 weeks)

PTO policy

Descrizione del lavoro

Fractal is seeking a Senior GenAI Engineer to design and maintain scalable AI platforms on AWS, focusing on Generative AI, Agentic AI, and RAG. You will lead the development of enterprise‑grade AI solutions, integrate multi‑agent workflows, and drive foundation model integrations with Bedrock.

The role emphasizes governance, observability, security, and scalable software engineering practices, with mentorship of engineers and collaboration across teams. Cambridge, MA onsite opportunity.

Competenze

• 8–10 years of software engineering experience with at least 3+ years in GenAI/AI solution development.
• Strong hands‑on experience building production‑grade Generative AI solutions.
• Expertise in Agentic AI, AI Agents, multi‑agent architectures, tool calling, function calling, orchestration.
• Strong experience designing and implementing RAG architectures, including embeddings and vector databases.
• Hands‑on experience with Amazon Bedrock, model orchestration, prompt engineering, and deployment patterns.
• Deep understanding of LLMs, evaluation, and deployment patterns.
• Strong proficiency in Python backend development and API implementation.
• Experience with AWS services (Bedrock, Lambda, ECS/EKS, S3, CloudWatch, DynamoDB, OpenSearch).
• Experience with Terraform and IaC for cloud automation.
• Experience with Docker, Kubernetes, and CI/CD pipelines.
• Knowledge of AI observability, telemetry, and monitoring.
• Knowledge of relational, NoSQL, vector, and graph databases.
• Experience with security, governance, and responsible AI frameworks.

Mansioni

• Design, develop, and maintain scalable GenAI platforms on AWS.
• Architect and implement multi‑agent AI solutions and tool integrations.
• Design RAG solutions using embeddings, vector stores, and semantic search.
• Build AI applications on Bedrock for inference and orchestration.
• Develop reusable platform components, APIs, and accelerators.
• Create knowledge graphs and vector databases for AI use cases.
• Create evaluation benchmarks for quality, latency, and safety.
• Implement governance, guardrails, and compliance controls.
• Develop observability with telemetry, monitoring, and dashboards.
• Build cloud‑native microservices and APIs using Python.
• Automate infrastructure with Terraform and IaC practices.
• Develop CI/CD pipelines for AI and cloud workloads.
• Collaborate with cross‑functional teams to drive adoption.
• Mentor junior engineers and contribute to architecture reviews.

Conoscenze

GenAI Solutions

Agentic AI

LLM Knowledge

Python Backend

AWS Cloud

Terraform IaC

CI/CD Pipelines

Observability

Security & Governance

Architecture Leadership

Strumenti

Amazon Bedrock

Terraform

Docker

Kubernetes

OpenSearch

LangChain

OpenTelemetry

MLflow

Grafana

Prometheus

Neo4j

Descrizione del lavoro

It's fun to work in a company where people truly BELIEVE in what they are doing!

We're committed to bringing passion and customer focus to the business.

Senior GenAI Engineer

Fractal Analytics is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite empowers imagination with intelligence. And that it will be such Fractalites that will continue to build the company for the next 100 years.

Please visit Fractal | Intelligence for Imagination for more information about Fractal.

Location: Onsite Cambridge, MA

Role Summary

We are looking for an experienced GenAI Senior Engineer to design, build, and maintain scalable, secure, and production-grade AI platforms and applications. The role will focus on Generative AI, Agentic AI, Retrieval-Augmented Generation (RAG), AWS Cloud, and modern platform engineering practices. The ideal candidate should possess deep expertise in designing enterprise‑grade AI solutions using Amazon Bedrock, LLM orchestration frameworks, cloud-native architectures, and infrastructure automation.

The candidate will play a key role in enabling enterprise teams to develop, deploy, monitor, and govern AI applications while ensuring scalability, security, observability, and operational excellence.

Key Responsibilities

• Design, develop, and maintain scalable, secure, and highly available GenAI platforms and AI-powered applications on AWS.
• Architect and implement Agentic AI solutions, multi-agent systems, tool integrations, function calling, and workflow orchestration frameworks.
• Design and implement enterprise-grade RAG (Retrieval-Augmented Generation) solutions using embeddings, vector databases, semantic search, reranking, and knowledge retrieval techniques.
• Build AI applications leveraging Amazon Bedrock for LLM inference, model orchestration, prompt management, and foundation model integrations.
• Develop reusable AI platform components, SDKs, APIs, accelerators, and reference architectures.
• Build knowledge-driven AI systems utilizing vector stores, graph databases, and knowledge graph technologies.
• Create evaluation and benchmarking frameworks to measure AI quality, accuracy, latency, safety, and performance.
• Implement AI governance, security controls, responsible AI practices, guardrails, and compliance mechanisms.
• Develop observability capabilities including telemetry, monitoring, tracing, logging, and operational dashboards.
• Design and develop cloud-native microservices and APIs using Python and modern software engineering practices.
• Automate cloud infrastructure provisioning and deployment using Terraform and Infrastructure as Code (IaC) principles.
• Build and maintain CI/CD pipelines for AI and cloud workloads.
• Collaborate with cross‑functional engineering, security, product, and business teams to drive AI platform adoption and best practices.
• Mentor junior engineers and contribute to architecture reviews and technical leadership initiatives.

Required Skills

• 8–10 years of software engineering experience with at least 3+ years in GenAI/AI solution development.
• Strong hands‑on experience building production‑grade Generative AI solutions.
• Expertise in Agentic AI, AI Agents, multi‑agent architectures, tool calling, function calling, orchestration, and MCP (Model Context Protocol).
• Strong experience designing and implementing RAG architectures, including embeddings, vector databases, retrieval pipelines, reranking, and semantic search.
• Hands‑on experience with Amazon Bedrock, foundation model integration, inference optimization, prompt engineering, and model orchestration.
• Deep understanding of Large Language Models (LLMs), prompt engineering, evaluation, model selection, and deployment patterns.
• Strong proficiency in Python for backend development, AI application development, and API implementation.
• Strong experience with AWS Cloud Services such as Bedrock, Lambda, ECS/EKS, API Gateway, S3, IAM, CloudWatch, DynamoDB, OpenSearch, Step Functions, and related services.
• Experience with Terraform and Infrastructure as Code (IaC) for cloud automation and platform deployment.
• Experience building cloud-native applications using APIs, Microservices, Docker, Kubernetes, and CI/CD pipelines.
• Understanding of AI observability, monitoring, tracing, and telemetry.
• Knowledge of relational, NoSQL, vector, and graph databases.
• Experience with security, governance, compliance, and responsible AI frameworks.

Preferred/Good-to-Have Skills

• LangChain, LangGraph, Semantic Kernel.
• LlamaIndex.
• OpenAI Agents SDK or similar agent frameworks.
• Amazon OpenSearch, Pinecone, Weaviate, Chroma, FAISS, or similar vector database technologies.
• OpenTelemetry, Langfuse, Arize Phoenix, MLflow.
• Grafana, Prometheus, CloudWatch Observability.
• Neo4j and knowledge graph technologies.
• Experience with distributed systems and scalable platform engineering.
• Experience with MLOps, LLMOps, and AI deployment pipelines.
• Exposure to fine‑tuning, model evaluation, and AI benchmarking frameworks.

Soft Skills

• Strong communication and stakeholder management skills.
• Excellent problem‑solving and analytical thinking.
• Ability to collaborate effectively across engineering, security, architecture, and product teams.
• Strong ownership and accountability mindset.
• Technical leadership, mentoring, and architecture guidance capabilities.
• Strong documentation and knowledge‑sharing practices.
• Ability to work independently in a fast‑paced client‑facing environment.

Key Technologies

GenAI, Agentic AI, RAG, Amazon Bedrock, AWS Cloud, Python, Terraform, LangChain, LangGraph, LlamaIndex, OpenSearch, Vector Databases, Docker, Kubernetes, CI/CD, MCP, AI Observability, LLMOps, Microservices, Knowledge Graphs.

Pay

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Fractal, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is: $120,000-$150,000. In addition, for the current performance period, you may be eligible for a discretionary bonus.

Benefits

As a full‑time employee of the company or as an hourly employee working more than 30 hours per week, you will be eligible to participate in the health, dental, vision, life insurance, and disability plans in accordance with the plan documents, which may be amended from time to time. You will be eligible for benefits on the first day of employment with the Company. In addition, you are eligible to participate in the Company 401(k) Plan after 30 days of employment, in accordance with the applicable plan terms. The Company provides for 11 paid holidays and 12 weeks of Parental Leave. We also follow a "free time" PTO policy, allowing you the flexibility to take time needed for either sick time or vacation.

Fractal provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

If you like wild growth and working with happy, enthusiastic over‑achievers, you'll enjoy your career with us!