LLM Developer
LockedIn AI is the #1 real-time AI interview and meeting copilot, trusted globally by over 1 million users.
We build AI-powered systems that help candidates perform better in high-stakes career moments by providing real-time assistance during interviews and professional conversations.
Our platform sits at the intersection of:
- Large language models
- Real-time inference systems
- Retrieval systems and embeddings
- High-scale production infrastructure
Location
Manhattan, KS, USA, NY
Date Posted
Category
Agency
Job Type
Full Time
Political Affiliation
Democrat
Full-Time | Remote (US) · New York, NY
Department: AI / ML
Compensation: $150,000 – $220,000 USD / year
LockedIn AI is looking for a deeply technical LLM Developer to design, build, and optimize the large language model systems powering our real-time AI copilot used by over 1 million users.
This is a core engineering role where you will directly shape how our AI listens, reasons, and responds during live interviews, coding assessments, and professional meetings.
About LockedIn AI
LockedIn AI is the #1 real-time AI interview and meeting copilot, trusted globally by over 1 million users.
We build AI-powered systems that help candidates perform better in high-stakes career moments by providing real-time assistance during interviews and professional conversations.
Our platform sits at the intersection of:
- Large language models
- Real-time inference systems
- Retrieval systems and embeddings
- High-scale production infrastructure
Role Overview
As an LLM Developer, you will own the full lifecycle of LLM-powered systems — from model selection and prompt design to inference optimization and production deployment.
You will work on systems that must be fast, accurate, and context-aware in real time. Your work directly impacts user experience during live interviews.
You are expected to think deeply about model behavior, latency, cost, and output quality — and continuously improve all four.
Key Responsibilities
LLM Application Development
- Design and build production LLM features for real-time AI assistance
- Develop prompt chains, conversation flows, and tool-use systems
- Build retrieval-augmented generation (RAG) pipelines
- Create multi-model routing systems based on latency, cost, and task type
Inference & Performance Optimization
- Optimize real-time inference pipelines for low latency
- Implement streaming responses, caching, and batching strategies
- Improve token efficiency and context window management
- Reduce cost through model routing and optimization techniques
Fine-Tuning & Model Customization
- Fine-tune models for domain-specific use cases
- Build and manage training datasets and evaluation pipelines
- Apply techniques such as LoRA, QLoRA, and RLHF
- Run experiments to compare model performance across configurations
Prompt Engineering & Quality Systems
- Design system prompts and instruction architectures
- Build evaluation frameworks for hallucination, accuracy, and relevance
- Perform root-cause analysis of model failures
- Continuously iterate on prompt and retrieval strategies
Evaluation & Monitoring
- Build LLM evaluation pipelines and benchmarks
- Monitor production metrics including latency, quality, and cost
- Detect model drift and regressions
- Optimize token usage and API efficiency
Safety & Reliability
- Implement guardrails against prompt injection and unsafe outputs
- Test adversarial inputs and edge cases
- Ensure privacy-first handling of user data
- Improve robustness of real-time AI responses
Required Qualifications
- 3+ years experience building LLM or AI systems in production
- Strong experience with RAG systems and prompt engineering
- Proficiency in Python and LLM frameworks (LangChain, LlamaIndex, or similar)
- Strong understanding of transformer architectures
- Experience with vector databases and embeddings pipelines
- Experience building APIs or backend systems for AI services
- Experience with evaluation and monitoring of ML systems
Preferred Qualifications
- Experience with real-time or low-latency LLM systems
- Background in speech + multimodal AI systems
- Experience with agentic workflows and tool-use LLMs
- Familiarity with model compression and optimization
- Experience with LLM safety, guardrails, and adversarial testing
- Contributions to open-source AI or LLM projects
- Startup or early-stage company experience
What We Offer
Equity
Meaningful early-stage ownership in the company
Impact
Your work directly powers a platform used by over 1 million users
Flexibility
Remote-first culture with optional collaboration in New York City
Growth
Fast-paced environment focused on applied AI innovation
Culture
User-obsessed, engineering-driven, and execution-focused team
Why Join Us
- Category-defining AI copilot product
- Massive global user base
- Direct ownership of core LLM systems
- Opportunity to build real-time AI at scale
- Work at the frontier of applied large language models
How to Apply
Please submit:
- Resume or CV
- Short note including:
- Why you want to join LockedIn AI
- Whether you have used our product
- What improvements you would suggest
- Optional: GitHub, portfolio, or technical writing samples