AI Engineer

Job RequirementP&F Solutions is seeking a highly skilled AI Engineer with deep expertise in Natural Language Processing (NLP) and Generative AI, including hands-on experience with LLM development, intelligent agent creation, and cloud-based ML platforms such as AWS SageMaker, AWS Bedrock, Azure Machine Learning, and Google Vertex AI.This individual will play a key role in designing, building, and deploying production-grade AI solutions, helping to operationalize advanced language models that power automation, intelligent agents, and personalized user experiences across industries.Key Skills & Experience5+ years of professional experience developing AI/ML models, with a strong focus on natural language understanding, text generation, semantic search, and conversation modeling.Deep understanding of transformer-based architectures (e.g., BERT, GPT, T5, LLaMA, Claude, Gemini).Hands-on experience with:Fine-tuning and instruction tuning of LLMs on domain-specific data.Embedding models and vector databases for semantic retrieval and RAG pipelines.Prompt engineering, zero-shot, few-shot, and chain-of-thought prompting techniques.Experience designing and implementing LLM-powered agents capable of multi-step reasoning, tool invocation, and external API interactions.Familiar with agent frameworks and orchestration tools like:LangChain, Haystack, Semantic Kernel, or AutogenFunction-calling APIs (e.g., OpenAI tools, Bedrock Agents)Tool use, memory management, and dynamic context planningBuilt or contributed to chatbots, workflow assistants, or domain-specific copilots using both open-source and commercial models.Strong experience deploying NLP and GenAI workloads on:AWS SageMaker – model training, tuning (Hyperparameter/AutoML), multi-model endpoints, and Pipelines.AWS Bedrock – orchestration of foundation models (e.g., Anthropic, Cohere) into business workflows.Azure Machine Learning – endpoint management, AutoML, and integration with Azure OpenAI.Google Vertex AI – training/evaluation pipelines, model registry, and PaLM/Gemini model use.Skilled at deploying models as APIs using FastAPI, Flask, or managed endpoints.Implemented CI/CD pipelines for ML using SageMaker Pipelines, Vertex Pipelines, or GitHub Actions.Experienced in the full ML lifecycle: from data acquisition and preprocessing to monitoring and feedback loops.Proficient in:Model tracking and versioning (e.g., MLflow, DVC)Drift detection, model monitoring, and performance loggingData pipelines with tools like Airflow, AWS Step Functions, Glue, or BigQueryAware of best practices in responsible AI, including bias detection, fairness auditing, explainability (SHAP, LIME), and GDPR/AI Act compliance.Proven success working cross-functionally with data scientists, software engineers, DevOps, product managers, and business stakeholders.Ability to turn ambiguous business problems into deployable AI solutions, with measurable KPIs.Strong written and verbal communication skills — capable of presenting complex AI concepts in simple terms for executives or non-technical teams.Preferred CertificationsAWS Certified Machine Learning – SpecialtyAzure AI Engineer AssociateGoogle Professional Machine Learning EngineerBonus ExperienceWorking knowledge of:Enterprise LLM deployments using guardrails, moderation APIs, and fallback strategiesNLP/LLM CertificationsTensorFlow Developer or PyTorch SpecialistIf you are interested in this position, please send your resume to careers@pafsolutions.com. Please include "AI Engineer" in the subject line. We look forward to hearing from you!J-18808-Ljbffr