DCG

Prompt Engineer / Agent LLM Specialist

25.2k - 27.7k PLN25 200 - 27 700 PLN/ mies./ mies.B2BB2B (netto)

SeniorHybryda·WarszawaFull-time·B2B

#346772·Dodano 6 miesięcy temu·10

Źródło: SOLID.Jobs

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Tech Stack / Keywords

LLMJSONCI/CDAzure Open AIRAG

Firma i stanowisko

DCG is a space where business needs and people's ambitions meet. They help candidates find environments to develop their skills and assist companies in building effective teams by closely listening and responding to what matters to them, creating lasting and valuable relationships.

Wymagania

Experience in projects with agent-based LLM systems in regulated environments (e.g., banking) including PoC, pilot, and UAT
Practical knowledge of Azure OpenAI in enterprise environments and experience with reasoning models (e.g., o-series, Claude Extended Thinking)
Designing and developing prompts as "prompt as code" — versioning in Git, code review, CI/CD, regression tests, dev/test/prod environments
Designing modular prompts and agent architectures (ReAct, planning, self-check, multi-agent orchestration)
Knowledge of RAG and grounding — designing solutions based on knowledge sources, regulations, procedures, and client documents
Creating prompts resistant to hallucinations, prompt injection, and other security risks
Integrating AI solutions with business systems and agent orchestration tools
Evaluation methods for models and prompts: golden datasets, eval sets, regression testing, LLM-as-a-judge, quality and stability metrics
Experience with tools like LangSmith, Langfuse, Braintrust, Promptfoo or own evaluation frameworks
Analyzing agent traces, debugging failure modes, and iterative improvement based on runtime data

Nice to have:

CI/CD
Azure Open AI
RAG

Obowiązki

Designing prompts resistant to hallucinations; separation of trusted/untrusted data
Modular prompts: roles, instructions, constraints, output schema; reusability, parameterization, versioning
System of prompts for agents with tool access; precise tool descriptions
Designing outputs compatible with downstream: JSON, decision schemas, tables, validatable structures
Multi-agent orchestration: supervisor/worker patterns, agent specialization
Context management in long trajectories: compression, summaries, memory strategies
Prompts for RAG: citation patterns, grounding on sources, handling "no data"
Designing retrieval and context compression strategies per use case
Building golden datasets and evaluation sets for prompts and agent trajectories
Defining and measuring metrics: response quality, task success rate, tool-call accuracy, trajectory quality, stability, cost, time
LLM-as-a-judge: usage considering limitations and bias
Regression testing for prompt/model/API changes; participation in UAT
Working with Braintrust, LangSmith, Langfuse, Promptfoo or own evaluation harnesses
Identifying and mitigating risks: prompt injection, data exfiltration via tool use, jailbreaks, data disclosure

Benefity

25.2k–27.7k PLN net/month (B2B)
B2B contract with 100% flexible working hours
Hybrid remote work
Training budget and internal trainings
Medical package and sports package

Dofinansowanie szkoleń

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Opieka zdrowotna

Karta sportowa

DCG

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