Senior Network Test Engineer req. 1201873

BMA Group

• $110K — $130K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's or master's degree in a relevant field such as computer science, engineering, or AI
  • 7-10 years of professional experience in software development and AI
  • Strong understanding of networking principles and practices
  • Experience with large language models (LLMs) and AI agents
  • Proficiency in Python and microservices architecture
  • Familiarity with MLOps, including Docker and Kubernetes
  • Knowledge of data governance and compliance best practices

Responsibilities

  • Translate high-level designs into detailed APIs and service interfaces
  • Integrate LLMs and build robust AI pipelines and prompt strategies
  • Ensure timely delivery of features while maintaining documentation and code quality
  • Design evaluation metrics and conduct A/B tests for model performance
  • Implement ETL pipelines and enforce data governance standards
  • Containerize and deploy AI services, managing CI/CD processes
  • Monitor system performance and optimize AI systems for speed and reliability

Benefits

  • Comprehensive health and wellbeing benefits for employees and their families
  • Programs for personal and professional development to advance your career
  • Commitment to an inclusive workplace that values diverse backgrounds
  • Flexibility in managing work and personal responsibilities
  • Focus on teamwork and collaboration to achieve shared goals
Full Job Description
Job Description

Senior AI Software Developer

This role has been designed as 'Hybrid' with an expectation that you will work on average 2 days per week from an HPE office.

Job Description:

The Senior AI Engineer owns end-to-end delivery of AI features-from design to production-while raising the engineering bar through code quality, reliability, and mentoring. The engineer will convert architecture into robust implementations, proactively manage risks, and ensure observable, secure, and performant AI systems. Important to have Good Networking knowledge

Responsibilities: Solution Engineering & Delivery
• Translate high-level designs into clear component contracts, APIs, and service boundaries.
• Implement LLM integrations, RAG pipelines, agents, tool/function calling, and prompt strategies.
• Own feature delivery for sprints/releases; maintain high code quality and documentation.

Modeling & Evaluation
• Fine-tune models when needed; design evaluation harnesses and metrics.
• Build A/B testing setups; track accuracy, latency, robustness, and task success rates.
• Conduct error analysis; iterate using feedback efficacy loops and prompt refinement.

Data & Retrieval Engineering
• Build ETL/ELT pipelines; curate datasets with metadata, lineage, and validation.
• Implement vector indexing (chunking, embeddings, reranking), tune chunk size & overlap.
• Enforce data governance: PII handling, redaction, consent, auditability.

MLOps & Platform Readiness
• Containerize workloads (Docker); orchestrate deployments (Kubernetes/Helm).
• Own CI/CD for ML: train → evaluate → package → deploy → monitor → rollback.
• Maintain model/agent registries, experiment tracking, and reproducible environments.

Software Engineering & Integration
• Build microservices and async inference paths; support batch/stream processing.
• Integrate with enterprise auth, observability, telemetry, and logging.
• Write unit/integration/e2e tests, performance benchmarks, and failure-injection tests.

Observability, Reliability & Performance
• Instrument with metrics/logs/traces; define SLOs (latency, throughput, error rate).
• Optimize inference: batching, caching (KV cache), quantization, token efficiency.
• Implement guardrails (safety filters, jailbreak detection), auto-evals and alerts.

Security & Compliance
• Apply secure coding practices; manage secrets, encryption, and least privilege.
• Ensure compliance (data residency, consent, audit trails); respect IP policies.
• Enforce policy-based access and content safety in user-facing features.

Collaboration & Mentoring
• Review designs/PRs; coach L3 engineers on best practices.
• Coordinate with AI Architects, Data Engineers, QA, and Product.

Education and Experience Required:
• Bachelor's or master's degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline.
• Typically, 7-10 years' experience.

Knowledge and Skills:
• LLMs & Agents: Prompt engineering, function/tool calling, orchestration frameworks, RAG.
• ML/DS: Evaluation metrics (precision/recall, BLEU/ROUGE where relevant), error analysis.
• Data/RAG: Embeddings, similarity (cosine/IP), chunking, rerankers, vector DB operations.
• Backend: Python (FastAPI/Flask), microservices patterns.
• MLOps/Infra: Docker, Kubernetes, CI/CD, artifact management, GPU scheduling.
• Observability: Metrics/logging/tracing, dashboards, automated evaluation pipelines.
• Frameworks: PyTorch/TensorFlow, Hugging Face, LangChain/LlamaIndex.
• Data: Pandas, SQL/NoSQL, Parquet/Arrow, Kafka/queues.
• Vector DBs: FAISS, Milvus, pgvector, Pinecone, Weaviate.
• Ops: GitHub Actions/Azure DevOps, MLFlow/W&B

#LI-Hybrid

Additional Skills:

Artificial Intelligence Technologies, Cross Domain Knowledge, Data Engineering, Data Science, Design Thinking, Development Fundamentals, Full Stack Development, IT Performance, Machine Learning Operations, Scalability Testing, Security-First Mindset

What We Can Offer You:

Health & Wellbeing

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have - whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.

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