AI Developer

Job Title: Java Developer - Senior

Duration: Expected to be 12 months of a contract with possible of extension.
Location: Onsite Alpharetta GA - Hybrid
Pay Range: $55/hr. to $65/hr. . the pay rate may differ depending on your skills, education, experience, and other qualifications.
Featured Benefits:

• Medical Insurance in compliance with the ACA
• 401(k)
• Sick leave in compliance with applicable state, federal, and local laws

Job Description:

TOP 5 SKILLS REQUIRED:

• 5-7 years of experience in Python with 1-3 years of experience in Java
• Agentic / LLM Engineer experience using LangGraph agentic framework
• RAG / Knowledge graph
• AWS & Kubernetes
• Experience in AI observability platforms (Langsmith / Langfuse)

Core Software Engineering Skills Must Have)

• Strong coding in Python (often primary) and/or TypeScript/Java.
• Solid fundamentals: data structures, APIs, concurrency/async, error handling, clean architecture.
• Experience building microservices and integrating with internal/external APIs.
• Familiarity with CI/CD, automated testing, code reviews, and release management.

Agentic / LLM Engineering Skills (Must Have)

• Designing and implementing agent workflows: planning → tool selection → execution → verification.
• Tool/function calling patterns and building reliable tool interfaces (idempotency, retries, timeouts).
• Prompt engineering plus prompt/version management and safe prompt templating.
• Handling non-determinism: evaluations, guardrails, deterministic fallbacks, and replayable runs.
• Building multi-step orchestration (state machines, DAGs, workflow engines, or agent frameworks). Retrieval + Knowledge Integration (Often Required)
• Building RAG pipelines: chunking, embeddings, indexing, retrieval strategies, reranking.
• Working knowledge of vector databases (e.g., Pinecone, pgvector, FAISS, Weaviate) and search.
• Grounding and citation approaches; freshness and permission-aware retrieval. Reliability, Safety, and Governance
• Implementing guardrails: PII redaction, prompt injection defenses, policy filters, allow/deny tool lists.
• Designing for observability: tracing agent steps, tool calls, latency, token/cost metrics.
• Building robust fallbacks (rule-based flows, smaller models, cached answers, human escalation).
• Secure handling of secrets and credentials; least-privilege tool access. Evaluation & Quality (Critical for Agentic Systems)
• Creating evaluation suites: golden tasks, regression sets, scenario tests, adversarial tests. - Defining success metrics (task completion rate, groundedness, hallucination rate, latency, cost).
• Experience with A/B testing or online evaluation in production. Platform/Infrastructure (Preferred)
• Cloud experience (AWS/Azure/Google Cloud Platform), containers (Docker), optionally Kubernetes.
• Familiarity with scalable data pipelines and queues (Kafka/SQS/PubSub) for async agent work.
• Experience optimizing inference costs/latency (model choice, batching, caching, token reduction).

Nice-to-Have

• Experience with frameworks like LangChain, LlamaIndex, or workflow engines (Temporal, Step Functions, Airflow).
• Knowledge of security engineering relevant to LLM apps (prompt injection, data exfiltration patterns).
• Domain expertise in the product area (e.g., telecom operations, network management, customer support). Soft Skills - Strong cross-functional collaboration with product, security, and platform teams.
• Ability to translate business workflows into agent capabilities and measurable outcomes. - Comfortable operating in ambiguity and iterating from prototype → hardened production