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Anthropic Claude Code Data Jobs

3 jobs found

7d ago

Senior AI Engineer (SWE-3)

Leidos Linthicum Heights, MD

Linthicum Heights, MD

7d ago

$108k - $195k/yr Full time Senior Agile Ai Ml

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Job Description

Senior AI Engineer at Leidos, onsite in Linthicum Heights, MD, designs, develops, and deploys AI and ML tooling and LLM based capabilities to support the AI and Emerging Technologies mission.

Responsibilities

Mission Focus: Collaborate closely with technical leadership to design, develop, and maintain LLM orchestration frameworks that coordinate static analyzers, retrieval-augmented generation (RAG) systems, and automated testing pipelines. Develop and optimize data preprocessing pipelines to ingest, clean, transform, and vectorize product documentation, source code, and test results for LLM consumption. Design and implement database solutions to support RAG architectures, artifact storage, audit tra
Technical Proficiency: Collaboratively work with systems engineers to architect and deploy networked AI tools within secure enclaves and conduct performance profiling, optimization, and scalability analysis of mission systems. Support security assessments and authority to operate (ATO) processes.
Qualifications: Bachelor's degree plus eight (8) years of relevant experience or equivalent. Proficiency in Python, LLM integration, and data engineering. Experience with static analyzers, RAG framework, and relational and vector databases. Familiarization with Agile, Git, Jira, and Confluence.
Security Clearance: Active TS/SCI with Polygraph required.
Desirable Skills: Familiarization with Rust, Claude Code, Codex, and CI/CD.

Requirements

Bachelor's degree plus eight (8) years of relevant experience or equivalent.
Proficiency in Python, LLM integration, and data engineering.
Experience with static analyzers, RAG framework, and relational and vector databases.
Familiarization with Agile, Git, Jira, and Confluence.
Active TS/SCI with Polygraph required.

Technologies

Python
LLM integration
Data engineering
Static analyzers
RAG framework
Relational databases
Vector databases
Agile
Git
Jira
Confluence
Rust
Claude Code
Codex
CI/CD

Benefits

Paid Time Off
11 paid Holidays
401K with a 6% company match and immediate vesting
Flexible Schedules
Discounted Stock Purchase Plans
Technical Upskilling
Education and Training Support
Parental Paid Leave

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10d ago

Salesforce Technical AI Engineer (Senior Consultant, Technical Transformation)

Deloitte Arlington, VA

Arlington, VA

10d ago

$118k - $160k/yr Full time Anthropic Claude Code Artificial Intelligence Automation

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Job Description

Senior Salesforce Technical AI Engineer (Technical Transformation) at Deloitte, based onsite in Arlington, VA. This role leads the design, development, and deployment of Salesforce Public Sector solutions with GenAI integration, CI/CD, and government-client engagement in the Washington, DC region. The position requires a Bachelor’s degree and at least three years of relevant experience.

Responsibilities

Lead the end-to-end design, development, and deployment of advanced solutions using Salesforce Public Sector offerings and emerging capabilities such as Agentforce within mission-critical programs.
Establish and manage robust CI/CD pipelines and DevOps practices to ensure rapid and secure delivery.
Serve as a technical manager and hands-on innovator, embedding GenAI and modern AI practices directly into the development lifecycle to accelerate delivery and enhance system capabilities.
Work across the full technology stack, from backend integrations with large data platforms (Salesforce Data Cloud, Informatica, Databricks, Palantir Foundry) to frontend user experiences.
Collaborate directly with senior government clients, providing technical leadership and translating complex mission requirements into scalable, forward-looking solutions.

Requirements

Bachelor’s degree and a minimum of 3 years of relevant experience.
Ability to work independently as well as within a team environment.
Effective written and verbal communication skills.
Meticulous attention to detail and a commitment to high-quality work products.
Ability to build and sustain professional relationships.
Capability to lead projects or workstreams.
Proficiency in managing and prioritizing multiple tasks in a fast-paced setting.
Strong interpersonal skills and a professional demeanor.
Ability to meet deadlines consistently.
Experience mentoring others and providing clear guidance.

Technologies

Salesforce
Apex
LWC
Salesforce Data Cloud
Informatica
Databricks
Palantir Foundry
Agentforce
Slack
MuleSoft
Azure DevOps
Jenkins
GitLab
Claude Code
GitHub Copilot

Benefits

Compensation range: USD 118,000 - 160,000 per year
Discretionary annual incentive program

The Team

Deloitte's Government & Public Services GPS practice focuses on delivering impact through people, ideas, technology, and outcomes. The team serves federal, state, and local government clients as well as public higher education institutions, bringing a fresh perspective to help clients anticipate disruption, reimagine possibilities, and fulfill their mission promises. The Sales & Service offering designs and implements sales and service experiences, capabilities, and architectures required to translate customer strategies into tangible results.

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20d ago

Lead Principal Machine Learning Engineer

Oracle San Francisco, CA

San Francisco, CA

20d ago

Full time Senior Agent Orchestration AI

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Job Description

Lead technical ownership of OCI AI platform capabilities and enterprise, production-grade agentic AI systems on Oracle Cloud Infrastructure (OCI).

Responsibilities

Act as the senior technical owner of OCI AI platform capabilities, covering agent execution, inference systems, model serving, AI workflow orchestration, evaluation, and observability.
Design and deliver scalable agentic AI systems that can reason, plan, use tools, execute workflows, orchestrate multi-step tasks, and support safe human-in-the-loop escalation.
Develop production-grade services for tool calling, agent memory, context management, MCP integration, vector retrieval, multi-agent coordination, policy enforcement, and evaluation.
Steer architecture across distributed services optimized for low latency, high throughput, GPU efficiency, reliability, cost, operability, and secure multi-tenant operation.
Define service boundaries, APIs, data models, state management, consistency tradeoffs, failure modes, SLIs/SLOs, rollout strategies, and readiness criteria for AI platform services.
Guide technical strategy across infrastructure, platform, security, data, and application engineering teams, translating broad goals into multi-quarter plans with measurable milestones.
Integrate AI agents securely and reliably with enterprise APIs, cloud services, databases, identity systems, secrets management, and external systems.
Establish AgentOps and LLMOps practices for tracing, monitoring, evaluation suites, regression testing, experimentation, safety guardrails, prompt and tool versioning, and production reliability.
Assess and operationalize emerging technologies in generative AI, agentic workflows, inference optimization, long-context systems, reasoning models, AI developer tooling, and agentic-first development.
Promote engineering excellence through code and design reviews, test strategy, deployment automation, incident analysis, documentation, and AI-assisted development using tools like Codex, Claude Code, Cursor, Copilot, or equivalents.
Mentor staff and senior engineers, raise architectural standards, and influence OCI engineering practices without requiring direct management authority.
Own critical production outcomes including reliability, performance, security posture, cost efficiency, and supportability for delivered systems.

Requirements

Advanced degree (PhD, MS, or BS with equivalent practical experience) in computer science, AI/ML, engineering, or related field.
12+ years of professional software engineering experience with ownership of production systems, or equivalent impact at senior staff / principal level.
Proven track record as a staff, senior staff, principal, or equivalent technical leader influencing architecture and execution across multiple teams.
Deep experience designing, building, and operating high-scale distributed systems, cloud services, infrastructure platforms, or AI/ML platform services.
Hands-on experience with production AI systems, agentic AI applications, autonomous workflows, tool-using agents, multi-step orchestration, or multi-agent systems.
Practical experience with orchestration frameworks such as LangGraph, LangChain, CrewAI, AutoGen, LlamaIndex, or similar ecosystems.
Strong understanding of LLM application patterns including prompt design, structured outputs, function/tool calling, context management, RAG, memory, tool safety, and evaluation.
Proficiency in Python with ability to contribute production code, reviews, tests, and debugging in complex distributed environments.
Expertise with Kubernetes, Docker, cloud-native infrastructure, service-to-service communication, scalability, fault tolerance, observability, and performance analysis.
Experience defining SLIs/SLOs, production readiness criteria, incident response practices, monitoring, tracing, experiments, and reliability programs for AI or distributed systems.
Strong understanding of AI safety, governance, security, and operational risks for autonomous or semi-autonomous systems, including data handling, access control, auditability, and human accountability.
Excellent written and verbal communication, with proven ability to lead technical direction, resolve ambiguity, and influence senior stakeholders.

Technologies

Python
Kubernetes
Docker
LangGraph
LangChain
CrewAI
AutoGen
LlamaIndex
Model Context Protocol (MCP)
Oracle Cloud Infrastructure (OCI)
Codex
Claude Code
Cursor
Copilot

Preferred qualifications

Experience optimizing large-scale GPU inference or training workloads for latency, throughput, utilization, availability, and cost.
Experience building or operating model serving, inference gateways, agent runtimes, workflow engines, developer platforms, or internal AI productivity platforms.
Experience integrating AI systems with enterprise APIs, databases, cloud services, vector databases, embeddings, retrieval systems, identity systems, and policy enforcement layers.
Experience with LLM fine-tuning, long-context systems, reasoning models, model routing, caching, batching, quantization, or related generative AI research.
Experience building evaluation frameworks for agentic systems, including offline evals, online experiments, golden tasks, adversarial testing, regression gates, and observability dashboards.
Experience using AI-assisted software development tools such as Codex, Claude Code, Cursor, Copilot, or similar in large-scale engineering environments.
Track record of defining architectural standards, platform capabilities, or engineering practices adopted across multiple teams or organizations.
Experience in enterprise, cloud infrastructure, regulated, security-sensitive, or mission-critical environments.

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Anthropic Claude Code Data Jobs

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