Energy Jobline ZR
Overview
Energy Jobline is the largest and fastest growing global Energy Job Board and Energy Hub. We have an audience reach of over 7 million energy professionals, 400,000+ monthly advertised global energy and engineering jobs, and work with the leading energy companies worldwide. We focus on the Oil & Gas, Renewables, Engineering, Power, and Nuclear markets as well as emerging technologies in EV, Battery, and Fusion. We are committed to ensuring that we offer the most exciting career opportunities from around the world for our jobseekers. Company
Vichara is a Financial Services focused products and services firm headquartered in NY and building systems for some of the largest i-banks and hedge funds in the world. Key Responsibilities
Architecture & System Design Architect, design, and lead
multi-agent LLM systems
using
LangGraph, LangChain, and Promptfoo
for prompt lifecycle management and benchmarking.
Retrieval-Augmented (RAG) pipelines
leveraging
hybrid vector search
(dense + keyword) using
LanceDB, Pinecone, or Elasticsearch .
Define system workflows for summarization, query routing, retrieval, and response, ensuring minimal latency and high precision.
Develop
RAG evaluation frameworks
combining retrieval precision/recall, hallucination detection, and latency metrics — aligned with analyst and business use cases.
AI Model Integration & Fine-Tuning
Integrate
GPT-4o, PaLM 2, and open-weight models
(LLaMA, Mistral) for task-specific contextual Q&A.
Fine-tune transformer models (BERT,
SentenceTransformers ) for document classification, summarization, and sentiment analysis.
Manage prompt routing and variant testing using
Promptfoo
or equivalent tools.
Agentic AI & Orchestration
Implement
multi-agent architectures
with modular flows — enabling task-specific agents for summarization, retrieval, classification, and reasoning.
Design
fallback and recovery behaviors
to ensure robustness in production.
Employ
LangGraph
for parallel and stateful agent orchestration, error recovery, and deterministic flow control.
Data Engineering & RAG Infrastructure
Architect ingestion pipelines for structured and unstructured data — including financial statements, filings, and PDF documents.
Leverage
MongoDB
for metadata storage and
Redis Streams
for async task execution and caching.
Implement vector-based search and retrieval layers for high-throughput and low-latency AI systems.
Observability & Production Deployment
Deploy end-to-end AI systems on
AWS EKS / Azure Kubernetes Service , integrated with
CI/CD pipelines (Azure DevOps) .
Build comprehensive
monitoring dashboards
using
OpenTelemetry
and
Signoz , tracking latency, retrieval precision, and application health.
Enforce testing and regression validation using golden datasets and structured assertion checks for all LLM responses.
Cross-functional Collaboration
Collaborate with DevOps, MLOps, and application development teams to integrate AI APIs with
React / FastAPI -based user interfaces.
Work with business analysts to translate credit, compliance, and customer-support requirements into actionable AI agent workflows.
Mentor a small team of GenAI developers and data engineers in RAG, embeddings, and orchestration techniques.
Qualifications
Experience:
5+ years as an AI or ML Engineer
Required Skills & Experience
LLMs & GenAI:
GPT-4o, PaLM 2, LangGraph, LangChain, Promptfoo,
SentenceTransformers
RAG Frameworks:
LanceDB, Pinecone, ElasticSearch, FAISS, MongoDB
Agentic AI:
LangGraph multi-agent orchestration, routing logic, task decomposition
Fine-Tuning:
BERT / domain-specific transformer tuning, evaluation framework design
Infra & MLOps:
FastAPI, Docker, Kubernetes (EKS/AKS), Redis Streams, Azure DevOps CI/CD
Monitoring:
OpenTelemetry, Signoz, Prometheus
& Tools:
Python, SQL, REST APIs, Git, Pandas, NumPy
Nice-to-Have Skills
Knowledge of
Reranker-based retrieval
(MiniLM / CrossEncoder)
Familiarity with
Prompt evaluation and scoring
(BLEU, ROUGE, Faithfulness)
Domain exposure to
Credit Risk, Banking, and Investment Analytics
Experience with
RAG benchmark automation
and
model evaluation dashboards
Additional Information
If you are interested in applying for this job please press the Apply Button and follow the application process. Energy Jobline wishes you the very best of your next career move.
#J-18808-Ljbffr
Energy Jobline is the largest and fastest growing global Energy Job Board and Energy Hub. We have an audience reach of over 7 million energy professionals, 400,000+ monthly advertised global energy and engineering jobs, and work with the leading energy companies worldwide. We focus on the Oil & Gas, Renewables, Engineering, Power, and Nuclear markets as well as emerging technologies in EV, Battery, and Fusion. We are committed to ensuring that we offer the most exciting career opportunities from around the world for our jobseekers. Company
Vichara is a Financial Services focused products and services firm headquartered in NY and building systems for some of the largest i-banks and hedge funds in the world. Key Responsibilities
Architecture & System Design Architect, design, and lead
multi-agent LLM systems
using
LangGraph, LangChain, and Promptfoo
for prompt lifecycle management and benchmarking.
Retrieval-Augmented (RAG) pipelines
leveraging
hybrid vector search
(dense + keyword) using
LanceDB, Pinecone, or Elasticsearch .
Define system workflows for summarization, query routing, retrieval, and response, ensuring minimal latency and high precision.
Develop
RAG evaluation frameworks
combining retrieval precision/recall, hallucination detection, and latency metrics — aligned with analyst and business use cases.
AI Model Integration & Fine-Tuning
Integrate
GPT-4o, PaLM 2, and open-weight models
(LLaMA, Mistral) for task-specific contextual Q&A.
Fine-tune transformer models (BERT,
SentenceTransformers ) for document classification, summarization, and sentiment analysis.
Manage prompt routing and variant testing using
Promptfoo
or equivalent tools.
Agentic AI & Orchestration
Implement
multi-agent architectures
with modular flows — enabling task-specific agents for summarization, retrieval, classification, and reasoning.
Design
fallback and recovery behaviors
to ensure robustness in production.
Employ
LangGraph
for parallel and stateful agent orchestration, error recovery, and deterministic flow control.
Data Engineering & RAG Infrastructure
Architect ingestion pipelines for structured and unstructured data — including financial statements, filings, and PDF documents.
Leverage
MongoDB
for metadata storage and
Redis Streams
for async task execution and caching.
Implement vector-based search and retrieval layers for high-throughput and low-latency AI systems.
Observability & Production Deployment
Deploy end-to-end AI systems on
AWS EKS / Azure Kubernetes Service , integrated with
CI/CD pipelines (Azure DevOps) .
Build comprehensive
monitoring dashboards
using
OpenTelemetry
and
Signoz , tracking latency, retrieval precision, and application health.
Enforce testing and regression validation using golden datasets and structured assertion checks for all LLM responses.
Cross-functional Collaboration
Collaborate with DevOps, MLOps, and application development teams to integrate AI APIs with
React / FastAPI -based user interfaces.
Work with business analysts to translate credit, compliance, and customer-support requirements into actionable AI agent workflows.
Mentor a small team of GenAI developers and data engineers in RAG, embeddings, and orchestration techniques.
Qualifications
Experience:
5+ years as an AI or ML Engineer
Required Skills & Experience
LLMs & GenAI:
GPT-4o, PaLM 2, LangGraph, LangChain, Promptfoo,
SentenceTransformers
RAG Frameworks:
LanceDB, Pinecone, ElasticSearch, FAISS, MongoDB
Agentic AI:
LangGraph multi-agent orchestration, routing logic, task decomposition
Fine-Tuning:
BERT / domain-specific transformer tuning, evaluation framework design
Infra & MLOps:
FastAPI, Docker, Kubernetes (EKS/AKS), Redis Streams, Azure DevOps CI/CD
Monitoring:
OpenTelemetry, Signoz, Prometheus
& Tools:
Python, SQL, REST APIs, Git, Pandas, NumPy
Nice-to-Have Skills
Knowledge of
Reranker-based retrieval
(MiniLM / CrossEncoder)
Familiarity with
Prompt evaluation and scoring
(BLEU, ROUGE, Faithfulness)
Domain exposure to
Credit Risk, Banking, and Investment Analytics
Experience with
RAG benchmark automation
and
model evaluation dashboards
Additional Information
If you are interested in applying for this job please press the Apply Button and follow the application process. Energy Jobline wishes you the very best of your next career move.
#J-18808-Ljbffr