Location: United States Experience: No minimum stated Job Type: Permanent Compensation: $300K - $350K
### Top Skills & Technologies LLM | MCP | RAG | APIs | Agentic Systems | Vector Database | AI Evaluation | AI Security
### Job Summary Thinking Minds' client is seeking a hands-on engineer to design, build, and operationalize AI and agentic systems alongside customer engineering teams. This role spans models, inference, tools, context, evaluation, security, observability, and production infrastructure. You will turn ambiguous challenges into working systems and translate recurring customer needs into reusable platform capabilities, reference architectures, and developer workflows.
### Ideal Candidate Should Have
Strong engineering fundamentals, technical depth, curiosity, judgment, and end-to-end ownership.
Confidence writing code, debugging agent traces, discussing architecture, and collaborating directly with customer engineers.
An understanding that dependable AI requires systems engineering, data, evaluation, reliability, APIs, and security-not prompts alone.
Comfort experimenting, benchmarking, and shipping while requirements are still evolving.
### Key Responsibilities
Build production workflows using LLM applications, agents, MCP integrations, APIs, tool calling, RAG, vector search, structured outputs, and multimodal models.
Design agents that reason across enterprise data, tools, and workflows while respecting identity, permissions, policy, and execution controls.
Explore foundation models, model routing, inference, prompt and context engineering, and fine tuning, balancing quality, latency, cost, and reliability.
Develop evaluations covering task success, tool correctness, hallucination detection, regression testing, safety, latency, and cost.
Implement observability, tracing, guardrails, fallback strategies, rate limits, retries, caching, and model gateways for reliable operation.
Improve retrieval, memory, grounding, and context windows through Embedding strategies, embeddings, vector databases, and appropriate enterprise data access.
Secure agent actions through authentication, authorization, secrets management, API access, policy enforcement, human approval, and auditability.
Own architecture, prototypes, integration, debugging, evaluation, and production delivery; feed recurring lessons into platform capabilities, APIs, gateways, identity services, and developer experience.
### Required Qualifications
Demonstrated ability to build and troubleshoot software systems with strong engineering fundamentals.
Practical AI fluency and understanding of production reliability, evaluation, context management, and secure tool execution.
Ability to explain architectural tradeoffs and work effectively with AI teams, platform teams, developers, and engineering leaders.
Strong problem-solving skills and willingness to remain close to implementation throughout delivery.
### Preferred Qualifications
Background in applied AI, agentic systems, AI infrastructure, distributed systems, developer platforms, security, ML infrastructure, inference, or model platforms.
Experience converting customer-specific solutions into reusable primitives and reference architectures.
Familiarity with retrieval-quality improvements and production agent evaluation frameworks.
Thinking Minds' client offers competitive equity, comprehensive medical coverage, flexible PTO, wellness reimbursement, a lunch stipend, and a collaborative engineering environment.
#Dice
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 10109241
- Position Id: 86895
- Posted 3 hours ago
