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Senior AI Engineer, Agentic Systems
Bot Jobs
2 hours ago
Full-time
On-site
Myrtle Point, Oregon, United States
THE COMPANY
Careerminds is a leader in career transition and coaching solutions, helping organizations support employees through change while enabling workforce growth and development. Our product portfolio includes market-leading Career Transition and Coaching Services as well as Progression, our application for Career Frameworks and progression planning.
THE ROLE We are developing a new product, an AI career companion app. It is distinct from our main platform and is in its early stages. At its heart is a conversational assistant which helps people with their job search, along with an agentic feature that enables it to carry out actions on their behalf such as updating a resume, searching for jobs, preparing for an interview, and following up on the outcome. You would have control of that core since the team is small and the direction has already been decided, most of the technical choices being yours.
This is a 100% remote/work-from-home role.
THE KEY RESPONSIBILITIES Conversation and Memory
A multi-turn assistant that maintains context across sessions over weeks or months
User memory and personalisation: what someone has shared, what they've done so far, what's changed
Retrieval over the coaching corpus, and fine-tuning if it turns out to be worth it
Conversation design: when the assistant should ask, suggest, act, or refer the user elsewhere
Agent Orchestration
Multi-step workflows with explicit state, tool calling and handoffs between specialized agents
Deciding which actions need user confirmation and which don't
Routing between model providers based on cost, latency and quality, with fallbacks
Traces for every agent decision so failures can be debugged
Evaluation
Offline evaluation sets for multi-turn conversations
LLM-as-judge scoring, validated against human ratings
Online experiments on live traffic, measured against user outcomes (applications, interviews, offers)
Safety
Guardrails for scope, tone and escalation in a consumer product
Prompt injection and jailbreak handling
GDPR and EU AI Act compliance as part of the design
Production
Streaming responses and latency work
Cost per conversation: caching, routing, prompt compression
Deployment: FastAPI, async Python, Postgres, Redis, AWS
THE MUST-HAVES
5+ years as a software or ML engineer, including at least 2 years shipping LLM-based products to real users
Experience building a conversational product that people used, and a clear account of what worked and what didn't
Production experience with agent frameworks (LangGraph or similar), tool calling, MCP, structured outputs, state management
Experience evaluating multi-turn systems: offline eval sets, judge validation, online testing
Experience with guardrails and adversarial input in a live product
Experience with streaming, latency and cost optimisation for LLM systems
Python, asynchronous programming, and API design; Git, Docker, and AWS.
Interest in the problem domain: careers, coaching, how people make decisions about work
THE NICE-TO-HAVES
Fine-tuning or post-training on conversational data (SFT, DPO, distillation)
Voice interfaces: STT, TTS, real-time conversational agents
Consumer product experience
Background in coaching, education, health or similar
MCP server development
Classical ML or recommendation systems
At Careerminds, we believe that diversity in thought and cultural background leads to better teams and stronger companies.
We seek talented, qualified employees, regardless of race, color, sex/gender (including pregnancy, gender identity, and gender expression), national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or any other protected classification under country or local law.
Careerminds is proud to be an Equal Employment Opportunity Employer.
Come join our team. Together, we'll help others tell their career stories and land their dream jobs.
#J-18808-Ljbffr
THE ROLE We are developing a new product, an AI career companion app. It is distinct from our main platform and is in its early stages. At its heart is a conversational assistant which helps people with their job search, along with an agentic feature that enables it to carry out actions on their behalf such as updating a resume, searching for jobs, preparing for an interview, and following up on the outcome. You would have control of that core since the team is small and the direction has already been decided, most of the technical choices being yours.
This is a 100% remote/work-from-home role.
THE KEY RESPONSIBILITIES Conversation and Memory
A multi-turn assistant that maintains context across sessions over weeks or months
User memory and personalisation: what someone has shared, what they've done so far, what's changed
Retrieval over the coaching corpus, and fine-tuning if it turns out to be worth it
Conversation design: when the assistant should ask, suggest, act, or refer the user elsewhere
Agent Orchestration
Multi-step workflows with explicit state, tool calling and handoffs between specialized agents
Deciding which actions need user confirmation and which don't
Routing between model providers based on cost, latency and quality, with fallbacks
Traces for every agent decision so failures can be debugged
Evaluation
Offline evaluation sets for multi-turn conversations
LLM-as-judge scoring, validated against human ratings
Online experiments on live traffic, measured against user outcomes (applications, interviews, offers)
Safety
Guardrails for scope, tone and escalation in a consumer product
Prompt injection and jailbreak handling
GDPR and EU AI Act compliance as part of the design
Production
Streaming responses and latency work
Cost per conversation: caching, routing, prompt compression
Deployment: FastAPI, async Python, Postgres, Redis, AWS
THE MUST-HAVES
5+ years as a software or ML engineer, including at least 2 years shipping LLM-based products to real users
Experience building a conversational product that people used, and a clear account of what worked and what didn't
Production experience with agent frameworks (LangGraph or similar), tool calling, MCP, structured outputs, state management
Experience evaluating multi-turn systems: offline eval sets, judge validation, online testing
Experience with guardrails and adversarial input in a live product
Experience with streaming, latency and cost optimisation for LLM systems
Python, asynchronous programming, and API design; Git, Docker, and AWS.
Interest in the problem domain: careers, coaching, how people make decisions about work
THE NICE-TO-HAVES
Fine-tuning or post-training on conversational data (SFT, DPO, distillation)
Voice interfaces: STT, TTS, real-time conversational agents
Consumer product experience
Background in coaching, education, health or similar
MCP server development
Classical ML or recommendation systems
At Careerminds, we believe that diversity in thought and cultural background leads to better teams and stronger companies.
We seek talented, qualified employees, regardless of race, color, sex/gender (including pregnancy, gender identity, and gender expression), national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or any other protected classification under country or local law.
Careerminds is proud to be an Equal Employment Opportunity Employer.
Come join our team. Together, we'll help others tell their career stories and land their dream jobs.
#J-18808-Ljbffr