AWS Bedrock Jobs

Figma is seeking an AI Engineer for its Internal AI team, which focuses on making AI adoption easier and more impactful for all Figmates across various departments like Sales, Support, Finance, People, and Legal. This role is a key part of the Applied AI Builds pillar, responsible for identifying high-value AI opportunities, prototyping solutions, and taking them to production. You will work directly with teams to understand business workflows, build AI agents and automations, integrate them with enterprise systems, and ensure their safe and reliable operation. This position involves owning solutions through production, determining the appropriate use of AI versus traditional software, and shaping how agents can safely interact with enterprise systems. You will also collaborate with platform teams to build reusable AI capabilities and help define Figma's approach to Applied AI engineering.

$153k - $296k

Turing builds the training and evaluation data that powers the world's leading frontier AI labs. As these labs push the boundaries of AI, they rely on us to assess their newest models against benchmark datasets, identify failure points, and determine what data will improve their capabilities. As a Field Engineer, AI Labs, you will be the technical representative of Turing to these frontier research teams, operating at the intersection of client-facing solutions engineering and hands-on AI evaluation. You will connect new model endpoints, execute comprehensive evaluations across Turing's datasets, synthesize performance metrics into actionable insights, and present these findings directly to client researchers and technical leaders. This is a high-velocity, high-agency role for a technically adept individual who excels at customer interaction, running benchmarks against model APIs, and ensuring precise data delivery.

$175k - $232k

Accenture

This role focuses on developing and optimizing AI agents and LLM-powered applications to enhance cybersecurity operations within a Security Operations Centre (SOC). The AI/ML Engineer will collaborate with security experts to design, build, and deploy AI workflows that integrate with existing security tools, aiming to accelerate threat detection and response. The mission is to leverage AI to combat evolving cyber threats, requiring a strong engineering background and a security-first mindset. The position involves architecting modular and scalable AI solutions, implementing robust security measures against adversarial attacks, and adhering to AI governance frameworks for data handling, logging, and compliance. Cost management for LLM usage and infrastructure is also a key aspect, alongside clear technical documentation.

Full time • San Francisco, CA • $180K – $240K • 2 openings Parameter builds AI agents that do offensive security work. Our agents run autonomous penetration tests against production applications and cloud environments, finding IDORs, broken access control, XSS, and infrastructure misconfigurations that scanners miss and that human pentest firms only look for once or twice a year. We are not a theoretical security company. Our team has responsibly disclosed real, high-severity vulnerabilities to well-known technology companies, and our findings are the front door to most of our customer relationships. You'll build the agent systems that do the actual hacking. That means designing the reasoning loops, tool interfaces, and memory architecture that let an LLM behave like a competent offensive security researcher rather than a fuzzer with good manners. The title points at where you'll spend most of your time. Expect the rest of the week to go wherever the work is: agent systems one day, the product the next, a customer call or a report that has to go out after that. We are small enough that everyone works across every product, and we hire people who want that. What you'll do - Design and ship agent workflows in LangGraph and Temporal that plan, execute, and verify multi-step exploitation chains - Build the tool layer the agents operate through: HTTP clients, auth handling, browser control, cloud enumeration, payload generation - Own the eval loop. We use Braintrust and Langfuse. You'll define what “good” means for agent runs and make the number go up - Reduce false positives, which is the single hardest problem in this space and the thing customers care most about - Manage inference cost and latency at scale, including prompt caching, context strategy, and model selection across Claude and Bedrock What we're looking for - 3+ years of software engineering, with at least one year building production LLM systems (not just prototypes or demos) - Strong TypeScript. Comfortable with async, distributed systems, and long-running workflow orchestration - Real intuition for context engineering, tool design, and why agents fail in the wild - You measure things. You've built or maintained an eval harness and know why offline metrics diverge from production behavior - Bonus: security background, CTF experience, bug bounty history, or a track record of breaking things you were not supposed to break Interview process - Intro call with a founder (30 minutes) - Technical deep dive on your past work (60 minutes) - Paid work trial or take-home, scoped to roughly one day - Onsite in San Francisco with the team - References and offer Stack TypeScript · LangGraph · Temporal · GCP · AWS Bedrock · Anthropic API · Langfuse · Braintrust · GitHub Actions · Linear · Graphite We move quickly. Our target is an offer within two weeks of first contact. Small team, high trust, extremely fast. If you want to see your work in front of customers within days, this is that. This role is onsite in San Francisco. You must be authorized to work in the US; we are not able to sponsor visas at this time.

$180k - $240k

The AI Platform team is building the shared runtime for all AI agents at MeridianLink, encompassing model gateway, orchestration, memory, and observability. This role focuses on the trust and explainability layer of this runtime, developing tracing, evaluation, and explanation capabilities. These features will enable engineers to understand multi-agent workflows and allow product teams to provide customers with appropriate explanations to build trust in agent outputs. This is a hands-on engineering role where you will write code for tracing agent actions, adopt and extend open-source frameworks for explainability and observability, and build primitives for surfacing explanations to end-users. You will work closely with a Staff engineer team lead and architects who will support your growth in this area.

$104k - $178k

Anthropic

The Safeguards ML Infra team is responsible for designing, building, and operating the production infrastructure that powers Claude's safety systems. This role is central to ensuring safeguards are properly configured and deployed for model launches, and owning the off-cycle deployment of new safety classifiers. The team ensures safety on the token generation path and manages the operational aspects of deploying these systems into production, including standing up safeguards for new model launches and deploying new safety classifiers. Every frontier model release goes through this team, which configures, verifies, and rolls out safeguards across all Claude platforms and leads incident response when issues arise. The goal is to automate manual checks into continuous validation and evolve launch runbooks into robust tooling.

$320k - $485k

Accenture

Accenture Industry X is seeking a Senior AI Full Stack Developer with expertise in Python and React/TypeScript to design, build, and deploy production-grade AI applications. You will work across the complete technology stack, from Python backend services and AI orchestration layers to responsive React-based user experiences. This role involves hands-on work with Large Language Models (LLMs), Generative AI, Agentic AI, Retrieval-Augmented Generation (RAG), APIs, cloud platforms, and modern DevOps practices, transforming AI concepts into scalable, observable, and production-ready solutions within fast-moving, cross-functional teams.