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Llamaindex Engineer Jobs

3 jobs found

5d ago

Senior AI Engineer

Flex Employee Services Irvine, CA

Irvine, CA

5d ago

$47 - $51/hr Full time Agentic Ai AI Ai Ml

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Job Description

The Senior AI Engineer role at Flex Employee Services focuses on designing, building, and scaling a production-grade Generative AI and Data Platform on AWS, with emphasis on LLM powered capabilities, vector search, graph-based knowledge systems, and governed data pipelines.

Responsibilities

Design and operationalize LLM powered applications using retrieval augmentation (RAG), embeddings, prompt orchestration, and evaluation frameworks.
Develop vector search solutions leveraging Amazon OpenSearch.
Build graph-based knowledge systems with Amazon Neptune.
Integrate AWS data stores such as ElastiCache (Redis) and DynamoDB to support AI workloads.
Construct agentic workflows using LangGraph, AutoGen, CrewAI, or equivalent frameworks.
Incorporate LangChain or LlamaIndex for retrieval orchestration, tool calling, and context management.
Define standards for tool integration and context sharing following MCP style designs.
Evaluate LLM models and retrieval strategies with a focus on latency, accuracy, cost, and context limits.
Design and build scalable data pipelines using Databricks and Apache Spark.
Develop data ingestion, transformation, document processing, embedding generation, and indexing pipelines.
Ensure data quality through validation, completeness, consistency, and ongoing monitoring.
Implement data governance, access controls, retention policies, auditability, and lineage tracking.
Develop secure and scalable backend services and APIs with robust design principles.
Define API standards, versioning, reliability, retry logic, circuit breakers, and idempotency.
Build reusable platform capabilities that serve multiple teams and applications.
Establish and manage CI/CD pipelines to support rapid development cycles.
Deploy production systems using Docker and Kubernetes, with blue/green, canary, rollback, and feature flag strategies.
Monitor platform reliability, observability, security, data freshness, and cost optimization.
Define and monitor GenAI quality metrics including grounding, retrieval relevance, response consistency, latency, and cost.
Implement prompt and version tracking, evaluation pipelines, and continuous improvement workflows.
Ensure AI security through access controls, authentication, data protection, responsible AI guardrails, privacy, and auditability.

Requirements

5+ years of experience in Generative AI and LLM work including RAG, embeddings, and prompt engineering.
Hands-on experience with AWS Cloud services such as OpenSearch, Neptune, DynamoDB, and ElastiCache/Redis.
Strong background in vector search and retrieval systems (OpenSearch or vector databases).
Proficiency with graph databases and knowledge graph concepts (Amazon Neptune).
Experience with LLM frameworks such as LangChain or LlamaIndex.
Experience with agentic AI frameworks like LangGraph, AutoGen, or CrewAI.
Experience building data pipelines with Databricks and Apache Spark (including embedding pipelines).
Backend/API development expertise in Python, including scalable APIs and microservices.
Proven track record of delivering production-grade Generative AI solutions.
Strong Python programming skills and familiarity with distributed systems, API design, and scalable backend development.
Experience building end-to-end AI/ML platforms and lifecycle delivery.
Education: Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related field.

Technologies

LangChain, LlamaIndex
LangGraph, AutoGen, CrewAI
OpenSearch, Amazon Neptune, DynamoDB
ElastiCache (Redis)
Databricks, Apache Spark
Python, Docker, Kubernetes

Benefits

Dental insurance
Health insurance
Referral program
Vision insurance

Preferred Skills

Model evaluation frameworks and LLM observability tools
AI governance and compliance frameworks
Kubernetes and advanced MLOps practices
Model Context Protocol (MCP) patterns
Agent-based architectures

Domain Experience

AI/ML Platform Engineering
Generative AI / LLM Applications
Data Platform / Big Data Engineering

Soft Skills

Strong problem-solving and analytical thinking
Ability to communicate complex AI concepts clearly
Collaborative and cross-functional mindset
Ownership-driven and proactive execution

Application Questions

Are you comfortable working on W2, or should you wait for a future 1099/C2C opportunity?
Are you willing to work on a contract basis, or should you wait for future full-time opportunities?
Do you have at least 5 years of experience with Graph Databases (Amazon Neptune, Knowledge Graphs)?
Do you have at least 5 years of experience with Agentic AI Frameworks (LangGraph / AutoGen / CrewAI)?
Do you have at least 5 years of experience with Databricks and Apache Spark (data pipelines, embedding pipelines)?
Do you have at least 5 years of experience with Backend/API Development (Python, scalable APIs, microservices)?
Do you have at least 5 years of experience with Generative AI / LLM (RAG, embeddings, prompt engineering)?
Do you have at least 5 years of experience with AWS Cloud (OpenSearch, Neptune, DynamoDB, ElastiCache/Redis)?
Do you have at least 5 years of experience with Vector Search and Retrieval Systems (OpenSearch / Vector DB)?

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13d ago

AI Engineer

Booz Allen Hamilton Fort Belvoir, VA

Fort Belvoir, VA

13d ago

$99k - $225k/yr Full time AI Ai Infrastructure Ai Ml

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Job Description

Responsibilities

Train, evaluate, deploy, and maintain data-driven models that improve over time.
Define the direction of critical solutions by selecting appropriate ML algorithms and technologies.
Partner with data engineers, data scientists, solutions architects, and MLOps to deliver scalable AI solutions, including large-scale data processing.
Guide clients through the landscape of AI and ML algorithms, tools, and frameworks.
Define AI strategy for national security customers.

Requirements

Experience in software engineering, ML engineering, and AI systems development using Python.
Experience building, deploying, and maintaining LLM-powered systems and complex data pipelines in production environments.
Experience implementing advanced prompting strategies, LangChain or LlamaIndex AI orchestration frameworks, vLLM or TGI LLM inference engines, and tool calling or agentic workflows.
Experience integrating AI components, including embeddings, vector databases such as LanceDB, pgvector, or Elasticsearch, and Retrieval-Augmented Generation (RAG) pipelines.
Ability to translate early-stage prototypes into robust, scalable production systems.
Ability to own system performance, continuously optimizing for latency, throughput, and reliability.
TS/SCI clearance.
Bachelor's degree.

Technologies

Python
LangChain
LlamaIndex
vLLM
TGI
LanceDB
pgvector
Elasticsearch
Docker
Kubernetes
AWS
Azure
GCP
Kafka
Retrieval-Augmented Generation (RAG) pipelines

Benefits

Health
Life
Disability
Financial
Retirement benefits
Paid leave
Professional development
Tuition assistance
Work-life programs
Dependent care
Recognition awards program

Clearance

Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information. TS/SCI clearance is required.

Identity verification

You will complete an identity verification process that uses advanced biometrics and artificial intelligence to ensure authenticity and prevent fraud.
Interviews and assessments will be conducted on camera.
Booz Allen may capture your image to verify identity and prevent fraud.

Candidate AI Usage Policy

AI is part of Booz Allen's daily workflow, with a commitment to responsible and ethical use of AI tools. The use of artificial intelligence or other tools to assist with interview responses is prohibited unless explicit permission is granted.

Work Model

This position is onsite, with work primarily performed at a Booz Allen office or a customer facility, allowing direct collaboration with colleagues and clients as required by the role.

Commitment to Non-Discrimination

All qualified applicants will receive consideration for employment without regard to disability, veteran status, or any other status protected by applicable law.

Compensation

Salary: USD 99,000 - 225,000 per year
Compensation is determined by factors including location, education, experience, skills, and contract requirements; postings close within 90 days from the posting date.

Posting timeline

This job posting will close within 90 days from the posting date.

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2mo ago

Senior Software Engineer, AI Solutions

Uncommon Schools New York, NY

New York, NY

2mo ago Closed

$121k - $142k/yr Full time Backend Developer Senior AI

This position is no longer accepting applications (closed Jun 24, 2026).

Job Description

Senior Software Engineer to lead vision setting and deployment of AI solutions across Uncommon Schools, translating business needs into scalable AI infrastructure, and mentoring developers while shaping generative AI adoption.

Responsibilities

Collaborate with stakeholders across Uncommon to elicit requirements and translate business challenges into detailed, end-to-end AI system specifications.
Design and architect AI solutions covering data flows, model selection, and integration patterns that balance innovation with reliability.
Partner with process owners, product managers, and system managers to align AI capabilities with user needs and organizational objectives.
Rapidly prototype and deliver proofs of concept and minimum viable products using large language models, retrieval augmented generation pipelines, and AI agent frameworks.
Architect and deploy production-grade AI agents to automate complex workflows, ensuring scalability, observability, and ongoing performance monitoring.
Build secure API integrations and data pipelines enabling AI systems to interact safely with core Uncommon databases while preventing errors and data hallucination.
Create reusable AI stack templates and low-code tooling to empower non-technical teams to build solutions autonomously.
Document AI environments, tools, and data flows to promote organizational clarity and consistency.
Collaborate with Data and IT product managers to define implementation pathways and cross-system data architectures.
Develop and maintain a library of prompt blueprints and AI implementation best practices for the organization.
Ensure full compliance with security audits for handling personally identifiable information in AI systems.
Provide coaching and support to adjacent teams on AI development methodologies and emerging best practices.

Requirements

Bachelor's degree in Computer Science, Data Science, Engineering, or equivalent professional experience.
Seven or more years of professional software development experience.
At least five years building integrations between applications using APIs.
Five or more years working with source control and continuous integration tools, including GitLab.
Proficiency in at least one programming or scripting language among Python, SQL, JavaScript/TypeScript, or Node.js.
Experience with iterative development practices, frequent testing, and incremental deployments.
Strong understanding of automation tools and software development life cycle methodologies.

Technologies

Python
SQL
JavaScript/TypeScript
Node.js
GitLab
LangChain
LlamaIndex
TensorFlow
PyTorch
AWS Bedrock
SageMaker
Google Cloud Vertex AI
dbt
Airflow
Retrieval-Augmented Generation (RAG)

Benefits

Paid time off of 19 days per year
Paid Winter and Summer org-wide holidays totaling 3 weeks
Health, Dental, and Vision insurance
403(b) retirement savings plan with employer match
Paid leave of absence options including parental, medical, and disability leave
Mental health and counseling support and wellness benefits
Pre-tax flexible spending, dependent care, and health savings accounts

Work Environment

Location: New York, NY, onsite at the Central Office in downtown Manhattan (100 Church Street) with a minimum of three days per week onsite
On-call availability for data infrastructure emergencies
Occasional after-hours work for data migrations, emergency pipeline fixes, and critical infrastructure maintenance
Minimal travel, including quarterly school visits and routine local travel within the region
Minimal physical demands; predominantly desk-based work

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