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3 jobs found

30d ago

Forward‑Deployed AI Engineer

Infosys Raleigh, NC

Raleigh, NC

30d ago Closed

Full time Backend Developer Ai Engineer Artificial Intelligence

This position is no longer accepting applications (closed Sep 16, 2026).

Job Description

As a Forward-Deployed AI Engineer at Infosys in Raleigh, NC, you will work with client and internal teams to support requirements, design, development, integration, testing, and production issue resolution. The role emphasizes stability and reliability throughout the software lifecycle.

Responsibilities

Contribute to the requirements elicitation process by documenting assigned portions of business requirements according to provided guidance.
Support software application design discussions and document design decisions to guide the technical team in delivering software solutions.
Participate in coding and integrate new features or updates into existing applications, with a focus on maintaining system stability.
Perform code reviews, implement code changes, and maintain code repositories.
Develop and apply test strategies, analyze results, and coordinate bug fixes to uphold software quality standards.
Create user training programs, documentation, and support frameworks to enable smooth transitions to new software applications.
Actively participate in resolving production issues and recommend preventive strategies to improve system reliability.
Maintain detailed records of code, testing techniques, and support activities to strengthen the knowledge base for related projects.

Requirements

A collaborative spirit and excellent communication skills.
Ability to manage end to end SDLC phases from requirement gathering through implementation.
Capability to translate complex requirements into actionable development tasks.
Interest in design paired with hands-on coding experience.
Proactive approach to testing, troubleshooting, and refining applications.
Ability to work with cross-functional teams and support software integration.

Your Contribution to the Team

Bring a collaborative spirit and strong communication skills to delivery efforts.
Handle end to end SDLC phases from requirement gathering to implementation.
Translate complex requirements into actionable development tasks.
Apply design thinking alongside hands-on coding experience.
Take a proactive approach to testing, troubleshooting, and application refinement.
Collaborate effectively with cross-functional teams and support software integration.

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1mo ago

Forward Deploy AI Engineer

David Joseph & Company San Francisco, CA

San Francisco, CA

1mo ago Closed

$200k - $300k/yr Full time Ai Driven Monitoring Ai Platform Artificial Intelligence

This position is no longer accepting applications (closed Aug 25, 2026).

Job Description

David Joseph & Company is seeking a forward-deployed AI engineer to weave its platform into customers' production environments, integrating monitoring and evaluation into real agent workflows and diagnosing live-system failures to push deployments toward stable production use. This role is highly client-facing, requiring clear, credible communication in addition to strong engineering depth. The position is based in San Francisco and is onsite, with five days in the office each week.

Responsibilities

Integrate the platform directly into customer production systems, coupling monitoring and evaluation with real agent workflows and diagnosing live-environment failures to enable reliable production deployments.
Collaborate closely with customers and communicate effectively, balancing engineering rigor with clear, accessible updates for technical and non-technical stakeholders.

Requirements

3–7 years of software engineering experience with a track record of shipping features end-to-end inside customer codebases.
Applied AI experience; AI-adjacent exposure preferred over a purely solutions-focused hire.
Strong customer-facing communication—able to explain complex concepts clearly and build trust with both technical and non-technical stakeholders.
Comfort deploying AI or LLM-based systems into real production environments.
Ability to translate ambiguous customer goals into concrete technical solutions.
The forward-deployed role is your genuine first choice, not a fallback.
Based in San Francisco or willing to relocate; in-person work required five days a week.
Aspiring to be a technical founder in the future.

Benefits

Founder training ground: own customer engagements end to end across real production systems, with the scope and autonomy of founding a technical company.
Deep technical and customer ownership on a fast, well-funded team shipping at high velocity with a sub-20-person organization.
Competitive compensation and perks: USD 200,000–300,000 salary, 0.1%–0.2% equity, full benefits, gym membership, private chef, and direct influence on the roadmap.

About the Company

Our client builds infrastructure for agent behavior monitoring. Where traditional observability focuses on logging, exceptions, and latency, this platform surfaces behavioral anomalies—instruction drift, context-retrieval loss, and hallucinations—in scaled production environments. Hundreds of teams building autonomous agents rely on it to understand how their systems behave post-deployment, turning real usage data into scoring and feedback loops that continuously improve agent reliability and performance. Founded 2024, the company remains under 20 people and operates in the AI infrastructure and observability space.

Details

Location: San Francisco, CA
Work policy: On-site, 5 days per week
Compensation: USD 200,000–300,000 per year plus 0.1%–0.2% equity
Visa sponsorship: H-1B, O-1, OPT considered case-by-case for exceptional candidates; main scope is candidates who don't require sponsorship
Employment type: Full-time

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1mo ago

AI Engineer - Forward Deployed Engineer Associate Manager

Accenture Irving, TX

Irving, TX

1mo ago Closed

$68k - $262k/yr Full time Manager AI Associate

This position is no longer accepting applications (closed Aug 17, 2026).

Job Description

This AI engineer role embeds with clients as technologist and trusted advisor, focusing on productionizing GenAI solutions on the Databricks Intelligence Platform and deploying agentic workflows at scale on cloud platforms.

Responsibilities

Embed directly with clients as technologist and trusted advisor; partner with stakeholders to define use cases, rapidly prototype, and deploy agentic workflows that are robust, secure, and operable in complex enterprise domains.
Design and engineer enterprise-ready AI agents covering retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability.
Build retrieval-augmented generation (RAG) and multi-agent systems on Databricks using Mosaic AI, Vector Search, Model Serving, and MLflow; govern data and models through Unity Catalog.
Develop data and feature foundations on the Lakehouse (Delta Lake, DLT, Unity Catalog) that feed production AI applications.
Tailor and deploy agentic applications across industries including finance, healthcare, and retail.
Lead design workshops, proofs of concept, and code-with sessions with client stakeholders.
Define and apply metrics to measure agent accuracy, latency, safety, and cost effectiveness.
Process large-scale distributed datasets on the Databricks Intelligence Platform with Apache Spark.
Integrate LLM solutions with APIs, model monitoring, and prompt management.
Operate MLOps and LLMOps pipelines with CI/CD across the ML and LLM lifecycle.

Requirements

Minimum 4 years of engineering experience on Databricks and large-scale big data projects (Delta Lake, DLT, Apache Spark, Unity Catalog); experience building API layers that expose data and AI/ML capabilities to enterprise systems.
Minimum 5 years of experience in Python, Java, or equivalent; comfortable with evaluation tooling, logging, monitoring, and observability.
Minimum 1 year of experience designing and shipping agentic AI solutions in production.
Minimum 1 year of experience shipping agentic solutions in production (agents, orchestration, context engineering, RAG, workflows) using AI platforms (OpenAI, Claude, Vertex AI, open source) and Databricks AI tooling (Mosaic AI, Vector Search, Model Serving, MLflow).
Minimum 2 years of experience shipping to production: CI/CD, infrastructure as code (Terraform, Helm), monitoring, and debugging; practical MLOps and LLMOps across the ML and LLM lifecycle (model training, serving, monitoring, prompt management).
Bachelor's degree or equivalent work experience (minimum 12 years); if Associate Degree, must have minimum 6 years work experience.

Technologies

Databricks Intelligence Platform
Mosaic AI
Vector Search
Model Serving
MLflow
Unity Catalog
Delta Lake
DLT
Apache Spark
HuggingFace
LangChain
DSPy
AWS
Azure
GCP
OpenAI
Claude
Vertex AI
Terraform
Helm
Python
Java

Benefits

Medical, dental, vision, life, and long-term disability coverage
401(k) plan
Bonus opportunities
Paid holidays
Paid time off

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