Applied AI Engineer

Applied AI Engineer at Nexera

Nexera Applied AI Engineer Remote

• Full time Company website Apply for Applied AI Engineer

As an Applied AI Engineer, you will build the application and knowledge layers of secure, self-hosted on-premises AI platforms. You will turn local models and customer-controlled data into the experiences people use every day: deep research over documents living on internal file servers, and AI-assisted software development inside the client’s own environment. You own the whole path from source document to useful answer: governed file-server connectors, extraction and OCR, indexing, hybrid retrieval, reranking, authorization, citations, evaluation, and the chat experience users actually touch. You will also configure and extend local coding assistants, agents, and safe tool integrations that help engineers understand repositories, make changes, and run real workflows. Deployments range from fully on-premises and air-gapped to hybrid architectures that pair local inference with cloud capacity. This is production AI software engineering, not just integration with existing AI platforms. You are building the experience layers that many of the frontier models and AI platforms provide today. We care about what you have built and what you have run in production operations, not necessarily how long you have been running it. Many strong candidates will have roughly three to five years building software, data platforms, search systems, developer tools, or AI applications, with hands-on LLM, RAG, enterprise search, agent, or local AI work. Years of experience are guidelines. We always look at actual work experience as the key indicator of experience and fit.

About Nexera

Nexera is an AI-native consulting firm that builds intelligent, custom solutions for organizations navigating the age of AI. We don't just talk about AI. We build with it, ship with it, and embed it into everything we deliver. Our engineers use the latest agentic development tools to move fast, solve hard problems, and create real business value for our customers. We are a fast-paced startup that is 100% focused on customer success. We invest in our people with cutting-edge tooling, continuous learning, and a culture that rewards pushing limits and driving innovation. If you want to work at the frontier of how software gets built and deployed, not just read about it, Nexera is the place.

Description

What You'll Do

Design and Build Applied AI Solutions

Create production AI applications that combine language models, enterprise data, retrieval, agents, tools, and user-facing workflows to solve real business and engineering problems.

Connect Enterprise Knowledge

Build reliable ingestion and integration pipelines that make documents, repositories, applications, and organizational data available to AI systems under the right access controls.

Engineer Retrieval and Grounding

Develop and improve search, RAG, reranking, context assembly, citation, provenance, and authorization patterns that produce relevant, traceable, trustworthy results.

Create User and Developer Experiences

Build chat, research, workflow, API, IDE, and developer-tool experiences that make advanced AI capabilities feel obvious in everyday work.

Evaluate and Operate AI Systems

Establish tests, evaluation frameworks, observability, security controls, feedback loops, and release practices that raise quality and reliability over time.

Partner and Transfer Knowledge

Work directly with clients, users, subject-matter experts, and engineering teams to define needs, communicate tradeoffs, ship working solutions, and enable long-term ownership.

Innovate How We Work

Experiment with and define the agentic workflows and tooling that improve how Nexera designs, builds, and evaluates AI applications. Your patterns become part of our operating model.

What We're Looking For

The bullets below are the profile we hire against; the Tools and Technologies section that follows is preferred, not required. If you meet most of what is here and can show real production work, we want to hear from you.

• Engineering experience that shows. Production software, data systems, enterprise search, developer tools, or AI-enabled products. Roughly three to five years, or equivalent capability you can demonstrate.
• Hands-on applied AI work. You have built LLM applications, RAG systems, search experiences, agents, or local AI integrations in production.
• Production software fundamentals. You can design maintainable services, data models, APIs, background workflows, tests, deployments, monitoring, and failure handling.
• Full-stack capability. Strong in Python or an equivalent backend language, and able to build or meaningfully contribute to a modern TypeScript/React experience.
• Retrieval judgment. Embeddings, lexical and vector search, hybrid retrieval, metadata filtering, reranking, chunking, and context construction, with an understanding of how to drive and improve both retrieval quality and answer quality.
• Data-pipeline discipline. You have worked with ingestion, ETL, synchronization, retries, backpressure, deduplication, schema evolution, revisions, deletions, and operational observability.
• Evaluation mindset. You can define representative test sets, pick metrics that mean something, run real error analysis, and build release gates that catch regressions before users do.
• Security and authorization awareness. You have a deep understanding of application security and you can reason about identity, ACLs, least privilege, data lifecycle, prompt injection, provenance, audit, and cross-user leakage.
• Product judgment. You care how streaming, sources, tool activity, errors, long-running work, and recovery feel to a user. You can turn complicated AI behavior into an experience people trust.
• Daily AI tool user. You already use AI tools (Claude, Claude Code, Copilot, Cursor, or similar) in how you code, research, and solve problems, and you can clearly show and demonstrate how you apply them to day-to-day engineering work.
• Relentless curiosity. You follow new model and tool releases because you find it interesting. You experiment on your own time. You have opinions about where this is going.
• Strong communication skills. You can work with users, subject-matter experts, client engineers, data owners, security teams, and program leaders to turn ambiguous needs into tested, supportable capabilities.
• Consulting mindset. You take ownership, communicate progress and risk early, document decisions, and adapt to the constraints of a client’s environment.
• U.S.

citizenship and residency

Required for this role due to the customer environments and information the work may support.

Military or cleared experience preferred

Prior U.S. military service, experience supporting defense or national-security organizations, and/or a current or previously held U.S. government security clearance are preferred but not required.

No clearance today is not a barrier

Nexera will sponsor clearance processing when assigned work requires it.

Tools and Technologies (Preferred)

You do not need every item below. Production judgment and transferable experience are what we will weigh and evaluate. A strong enterprise-search, data-platform, full-stack, or developer-tools engineer with credible applied AI work can be an excellent fit without the exact reference stack.

Backend and data

Python, FastAPI, Django or Flask, asynchronous workers and queues, PostgreSQL, SQL, Redis, REST APIs, SSE or WebSockets

Frontend and chat

TypeScript, React, Next.js or comparable frameworks, streaming chat interfaces, Markdown/code rendering, accessibility, responsive product development

Retrieval and search

pgvector, PostgreSQL full-text search, Elasticsearch/OpenSearch, Solr, Vespa, Qdrant, Weaviate, Milvus, FAISS, HNSW, IVFFlat, BM25, hybrid retrieval, rerankers

Document processing

IBM Docling, Apache Tika, Unstructured, OCR tools, PDF and Office parsing, scanned-document and multimodal pipelines

File services and identity

SMB/CIFS, NFS, Active Directory, POSIX or Windows ACLs, LDAP, FreeIPA, Keycloak, OIDC, JWT, row-level security

LLM applications and agents

LangGraph, LlamaIndex, LangChain, custom workflow engines, MCP clients and servers, structured output, tool calling, durable state, human approval and sandboxed execution

Evaluation and observability

Ragas, DeepEval, promptfoo, Phoenix, Langfuse, OpenTelemetry, Prometheus, Grafana, structured logging, golden-set and regression harnesses

User and research experiences

Open WebUI, LibreChat, Open Deep Research or comparable systems, citation and provenance interfaces, long-running research workflows

AI CLI and agentic tools

Claude Code, Gemini CLI, OpenAI Codex, GitHub Copilot

Developer experience

VSCodium or VS Code extensions, Cline, Continue, Tabby, aider, OpenHands, Goose

Additional differentiators

knowledge graphs, GraphRAG, Apache AGE or Neo4j, bi-temporal data models, multimodal retrieval, regulated or classified environments, and disconnected or air-gapped deployments

Position Details

Structure

Full-time or contract. We are flexible and will work out the right arrangement with the right person.

Location

Remote-first (US-based), with scheduled on-site work at client sites

Travel

Expect approximately 25% travel, concentrated around discovery, integration, user testing, deployment, and major project milestones, with lighter travel between them. On-site work is scheduled in advance wherever possible.

Eligibility

U.S. citizenship and current U.S. residency are required

Access Requirements

Must be willing and able to complete applicable customer background investigations, satisfy site-access and data-handling requirements, and obtain and maintain a U.S. government security clearance if required for assigned work

Compensation

Full-time base salary range

$165,000–$215,000, based on demonstrated experience, technical breadth, clearance status, and scope of responsibility, plus performance bonus.

Contract engagements

approximately $95–$150/hour (W-2) or $120–$175/hour (corp-to-corp), commensurate with experience, specialization, and clearance.

Benefits (Full-Time)

Time off

Flexible PTO plus federal holidays

Learning

Annual learning and certification budget, plus access to premium AI tooling (Claude Code and the frontier tools you will use daily)

Home office

Home-office setup

Travel comfort

Sensible travel policy — you book what makes the trip productive, and travel time is respected as work time

Our Hiring Process

We keep it fast and substantive — typically two to three weeks end to end:

Intro conversation (30 min)

your background, what you have built and shipped, and mutual fit

Technical deep-dive (60–90 min)

a working session on systems you have built — retrieval pipelines, LLM applications, agents, evaluation — plus how you use AI tools day to day

Scenario round (take away task)

walk through a realistic customer problem, from ambiguous need to shippable design, including how you would communicate tradeoffs to users and stakeholders

Final conversation with leadership, then a written offer

Salary

$165,000 - $215,000 per year

Apply for Applied AI Engineer

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