This is a remote position.

Location

Permanent Remote

Engagement Type

Fixed-Term Contract (6 Months) – *Dedicated Role (No Freelance/Ad-hoc)*

Start Date

Immediate ###

About the Project

Our Client is building custom internal AI agents and workflow automations to boost productivity across our Support, Sales, Customer Success, Recruiting, and Engineering teams. Our goal is to automate repetitive work—such as triage, summaries, follow-ups, and reporting—while enabling "copilot" experiences that help our teams execute faster with consistent quality.

This is a hands-on build role where you will integrate with our tools (Slack, Jira, Zoom, Email, Docs, CRM), implement agent workflows, and ship working automations quickly. ###

What You’ll Build (Key Use Cases)

You will focus on high-impact MVPs that can be deployed and improved in short iteration cycles. Examples include: -

Support & Engineering

An AI triage bot to classify bugs vs. change requests, ask required questions, and auto-create tickets with the correct fields. -

Sales & Customer Success

A Sales copilot that provides real-time answers grounded in product specs , and automations to generate follow-up emails, route them for approval, and send them. -

Recruiting

An interview evaluation agent that ingests transcripts to apply role rubrics and generate structured feedback. -

Internal Knowledge

Self-serve assistants and chatbots within Slack. ###

Key Responsibilities

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Agentic Workflow Design

Design and implement workflows involving tool calling, multi-step reasoning, and structured outputs. -

System Integration

Build robust integrations and connectors with common internal systems such as Slack, Jira, email, calendar, CRM, and data warehouses. -

RAG Implementation

Implement RAG (Retrieval-Augmented Generation) and knowledge systems for product and internal docs, ensuring citations and links to sources are included. -

Security & Access

Build basic access control patterns, including SSO/AD group-aware retrieval and role-based response filtering. -

Production & Guardrails

Ship MVPs fast, iterate based on user feedback, and add necessary guardrails such as evals, logging, and retry/timeout behaviors. -

Documentation

Document workflows and provide simple runbooks to facilitate internal adoption. * * * ###

Required Skills & Qualifications

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Software Fundamentals

Strong software engineering fundamentals with a focus on clean, testable code and a production mindset. -

LLM & Agent Experience

Proven experience building with LLMs and agents, specifically regarding prompting, structured output (JSON schemas), and tool/function calling. -

Orchestration

Experience with multi-step orchestration (agent loops, state machines, graphs). -

Frameworks

Hands-on experience with at least one major framework such as Claude Agent SDK / MCP, LangGraph, or OpenAI Assistants. -

API Integration

Strong experience with APIs and integrations (OAuth/SSO patterns are a plus). -

Workflow Engines

Familiarity with workflow engines like Temporal, Dagster, Airflow, or Prefect. -

Retrieval Systems

Experience with retrieval systems such as LlamaIndex, LangChain RAG, Elasticsearch, pgvector, or Pinecone. * * * ###

Tech Stack

We are flexible but expect a mix of the following: -

Languages

Python and/or TypeScript. -

Agent Frameworks

Claude Agent SDK and/or LangGraph. -

RAG

LlamaIndex or existing vector retrieval stacks. -

Integrations

Slack, Jira, Email, Call Recording, and CRM APIs. * * * ###

Success Metrics (First 2–4 Weeks)

• Deliver 1–2 production-ready MVP automations (e.g., interview evaluator or support triage bot).
• Establish basic observability including logs, failure handling, and simple admin runbooks.
• Create a clear plan for scaling to more use cases with reusable connectors.