The AI Engineer develops and deploys AI solutions, focusing on agentic systems, workflow automation, and integration while collaborating with senior engineers and clients.
AHEAD builds platforms for digital business. By weaving together advances in cloud infrastructure, automation and analytics, and software delivery, we help enterprises deliver on the promise of digital transformation.
At AHEAD, we prioritize creating a culture of belonging, where all perspectives and voices are represented, valued, respected, and heard. We create spaces to empower everyone to speak up, make change, and drive the culture at AHEAD.
We are an equal opportunity employer, and do not discriminate based on an individual's race, national origin, color, gender, gender identity, gender expression, sexual orientation, religion, age, disability, marital status, or any other protected characteristic under applicable law, whether actual or perceived.
We embrace all candidates that will contribute to the diversification and enrichment of ideas and perspectives at AHEAD.
Role Overview
The AI Engineer is a hands-on builder who develops and deploys agentic AI solutions for AHEAD’s clients. You will work on multi-agent workflows, retrieval pipelines, and system integrations that automate real business processes like document handling, SDLC tasks, service desk actions, reporting, and decision support.
This role focuses on implementing and improving components within larger agentic systems. You will collaborate closely with senior engineers, solution managers, and client teams to translate ideas into working automations. It is an ideal role for someone eager to deepen their skills in applied AI, workflow orchestration, and enterprise integration.
Key Responsibilities
- Agentic Solution Development
- Build and customize agents using frameworks such as LangChain, LangGraph, Autogen, CrewAI, or LlamaIndex.
- Implement components for document processing, workflow automation, data retrieval, and structured output generation.
- Develop and maintain vector DB pipelines (Pinecone, pgvector, Elasticsearch) and RAG-based retrieval workflows.
- Configure LLM/SLM endpoints, tool-calling functions, and agent memory/state handling.
- Workflow & Integration Engineering
- Implement real-time and batch workflows using Python, Kafka, EventBridge, Airflow, Celery, Snowflake, S3, or n8n.
- Build integrations with enterprise tools (SharePoint, Salesforce, ServiceNow, Jira, APIs).
- Support data transformations, validation, and versioning needed for downstream agent operations.
- Quality, Testing & Observability
- Write tests for agent behavior, pipelines, and model output consistency.
- Contribute to monitoring, logging, metrics, and guardrail configurations for agentic systems.
- Participate in debugging sessions and post-incident reviews with senior engineers.
- Client Delivery Support
- Participate in client workshops, demos, and working sessions as part of the engineering team.
- Translate requirements from senior engineers or solution managers into technical tasks and working components.
- Help document solution behavior, configurations, and deployment steps for clients.
- Security, Governance & Responsible AI
- Follow established patterns for access control, data handling, safe model usage, and auditing.
- Ensure compliance and guardrail configurations are consistently applied in implementations.
- Team Collaboration & Growth
- Contribute to internal documentation, code templates, and reusable building blocks.
- Learn and apply AHEAD’s reference architectures, best practices, and agentic patterns.
- Support onboarding of new engineers and collaborate in agile ceremonies.
Qualifications
- Required
- Solid Python programming skills and experience building APIs, batch jobs, or automation scripts.
- Exposure to multi-agent or LLM application frameworks (LangChain, LangGraph, Autogen, LlamaIndex, CrewAI).
- Familiarity with vector databases and retrieval workflows (Pinecone, pgvector, Elasticsearch).
- Experience with data engineering or workflow tools (Kafka, EventBridge, Snowflake, Airflow, Celery, AWS services, or similar).
- Strong attention to documentation, testing, and collaborative engineering practices.
- Ability to learn quickly in fast-moving, client-facing environments.
- Preferred
- Experience integrating with enterprise systems or SaaS platforms (ServiceNow, Salesforce, SharePoint, databases).
- Familiarity with MLOps, containerization, or observability stacks.
- Exposure to cloud services (AWS, Azure, GCP).
- Success Metrics
- High-quality implementation of agentic components, integrations, and workflows.
- Reliability and consistency of delivered features, validated through tests and monitoring.
- Steady velocity of delivery within agile teams.
- Strong collaboration with senior engineers and positive feedback from client teams.
- Demonstrated growth in agentic engineering skills and contribution to reusable assets.
Why AHEAD:
Through our daily work and internal groups like Moving Women AHEAD and RISE AHEAD, we value and benefit from diversity of people, ideas, experience, and everything in between.
We fuel growth by stacking our office with top-notch technologies in a multi-million-dollar lab, by encouraging cross department training and development, sponsoring certifications and credentials for continued learning.
USA Employment Benefits include:
- Medical, Dental, and Vision Insurance
- 401(k)
- Paid company holidays
- Paid time off
- Paid parental and caregiver leave
- Plus more! See benefits https://www.aheadbenefits.com/ for additional details.
The compensation range indicated in this posting reflects the On-Target Earnings (“OTE”) for this role, which includes a base salary and any applicable target bonus amount. This OTE range may vary based on the candidate’s relevant experience, qualifications, and geographic location.
Top Skills
Airflow
Autogen
Celery
Crewai
Elasticsearch
Eventbridge
Kafka
Langchain
Langgraph
Llamaindex
Pgvector
Pinecone
Python
S3
Snowflake
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