About Us
Automation Anywhere is the leader in Agentic Process Automation (APA) transforming how work gets done with AI-powered automation. Its APA system built on the industrys first Process Reasoning Engine (PRE) and specialized AI agents combines process discovery RPA end-to-end orchestration document processing and analyticsall delivered with enterprise-grade security and governance. Guided by its vision to fuel the future of work Automation Anywhere helps organizations worldwide boost productivity accelerate growth and unleash human potential.
Key Activities:
- Architect end-to-end AI/ML solutions tailored to business requirements ensuring scalability and performance.
- Experienced in use case discovery scoping and delivering complex solution architecture designs to multiple audiences requiring an ability to context switch in levels of technical depth across AI/ML technologies and platforms.
- Architect production level AI agent/RAG solutions for customers using our unified platform including end-to-end ML pipelines inference optimization integration with cloud-native services and MLOps
- Provide guidance and best practices to development teams on AI agent implementations.
- Serve as the trusted technical advisor for customers developing GenAI solutions such as RAG architectures on enterprise knowledge repo and ensure high-quality efficient and maintainable code for AI agents.
- Oversee the ingestion transformation and validation of large datasets for model training and deployment using AA or 3rd party hyper scaler platform.
- Implement and manage CI/CD pipelines for seamless model deployment and monitoring in production.
- Track and improve the performance of AI/ML systems through testing validation and iterative improvements.
- Stay updated on advancements in AI/ML and identify opportunities for integrating new techniques into solutions.
- Work closely with product managers data scientists and engineering teams to align on technical goals and deliverables.
- Create detailed architectural diagrams technical documentation and best practice guidelines.
- Address critical production issues and optimize system reliability and performance.
- Mentor team members and contribute to organizational learning in AI/ML technologies.
Skills & Qualifications Criteria:
Must Have Skills: - 7-10 yrs of overall IT experience with 5 years of experience in AI/ML implementations
- Deep knowledge of machine learning deep learning and natural language processing algorithms and frameworks (TensorFlow PyTorch Hugging Face etc.).
- Experience with the latest techniques in natural language processing including vector databases fine-tuning LLMs and deploying LLMs with tools such as HuggingFace Langchain and OpenAI
- Hands-on experience with AI/ML services on AWS GCP or Microsoft Azure. Have completed certifications from either of these hyper scaler providers.
- Strong programming skills in Python Java or other relevant languages;
- Familiarity with RAG (Retrieval-Augmented Generation) methodologies and integrating Generative AI into enterprise applications.
- Hands-on expertise in prompt engineering RAG vector DBs and technologies to implement AI agent solutions.
- Expertise in data preprocessing feature engineering and working with large-scale data pipelines (Apache Spark Kafka etc.).
Nice to have skills:
- Strong background on cloud services from various cloud service providers that integrates with AI/ML solutions
- Experience with MLOps tools like MLflow Kubeflow or SageMaker.
- Proficiency in deploying monitoring and optimizing models in production environments.
- Ability to design scalable secure and high-performance AI/ML solutions.
- Strong analytical skills to address complex technical challenges and innovate scalable solutions.
- Ability to articulate technical concepts to diverse audiences including non-technical stakeholders.
- Experience mentoring engineers and collaborating with cross-functional teams.
- Understanding of data privacy and AI ethics for compliant system designs.
All unsolicited resumes submitted to any @ email address whether submitted by an individual or by an agency will not be eligible for an agency fee.
Required Experience:
Unclear Seniority
About UsAutomation Anywhere is the leader in Agentic Process Automation (APA) transforming how work gets done with AI-powered automation. Its APA system built on the industrys first Process Reasoning Engine (PRE) and specialized AI agents combines process discovery RPA end-to-end orchestration docum...
About Us
Automation Anywhere is the leader in Agentic Process Automation (APA) transforming how work gets done with AI-powered automation. Its APA system built on the industrys first Process Reasoning Engine (PRE) and specialized AI agents combines process discovery RPA end-to-end orchestration document processing and analyticsall delivered with enterprise-grade security and governance. Guided by its vision to fuel the future of work Automation Anywhere helps organizations worldwide boost productivity accelerate growth and unleash human potential.
Key Activities:
- Architect end-to-end AI/ML solutions tailored to business requirements ensuring scalability and performance.
- Experienced in use case discovery scoping and delivering complex solution architecture designs to multiple audiences requiring an ability to context switch in levels of technical depth across AI/ML technologies and platforms.
- Architect production level AI agent/RAG solutions for customers using our unified platform including end-to-end ML pipelines inference optimization integration with cloud-native services and MLOps
- Provide guidance and best practices to development teams on AI agent implementations.
- Serve as the trusted technical advisor for customers developing GenAI solutions such as RAG architectures on enterprise knowledge repo and ensure high-quality efficient and maintainable code for AI agents.
- Oversee the ingestion transformation and validation of large datasets for model training and deployment using AA or 3rd party hyper scaler platform.
- Implement and manage CI/CD pipelines for seamless model deployment and monitoring in production.
- Track and improve the performance of AI/ML systems through testing validation and iterative improvements.
- Stay updated on advancements in AI/ML and identify opportunities for integrating new techniques into solutions.
- Work closely with product managers data scientists and engineering teams to align on technical goals and deliverables.
- Create detailed architectural diagrams technical documentation and best practice guidelines.
- Address critical production issues and optimize system reliability and performance.
- Mentor team members and contribute to organizational learning in AI/ML technologies.
Skills & Qualifications Criteria:
Must Have Skills: - 7-10 yrs of overall IT experience with 5 years of experience in AI/ML implementations
- Deep knowledge of machine learning deep learning and natural language processing algorithms and frameworks (TensorFlow PyTorch Hugging Face etc.).
- Experience with the latest techniques in natural language processing including vector databases fine-tuning LLMs and deploying LLMs with tools such as HuggingFace Langchain and OpenAI
- Hands-on experience with AI/ML services on AWS GCP or Microsoft Azure. Have completed certifications from either of these hyper scaler providers.
- Strong programming skills in Python Java or other relevant languages;
- Familiarity with RAG (Retrieval-Augmented Generation) methodologies and integrating Generative AI into enterprise applications.
- Hands-on expertise in prompt engineering RAG vector DBs and technologies to implement AI agent solutions.
- Expertise in data preprocessing feature engineering and working with large-scale data pipelines (Apache Spark Kafka etc.).
Nice to have skills:
- Strong background on cloud services from various cloud service providers that integrates with AI/ML solutions
- Experience with MLOps tools like MLflow Kubeflow or SageMaker.
- Proficiency in deploying monitoring and optimizing models in production environments.
- Ability to design scalable secure and high-performance AI/ML solutions.
- Strong analytical skills to address complex technical challenges and innovate scalable solutions.
- Ability to articulate technical concepts to diverse audiences including non-technical stakeholders.
- Experience mentoring engineers and collaborating with cross-functional teams.
- Understanding of data privacy and AI ethics for compliant system designs.
All unsolicited resumes submitted to any @ email address whether submitted by an individual or by an agency will not be eligible for an agency fee.
Required Experience:
Unclear Seniority
View more
View less