Forward Deployed Ai Engineer: Build Production Agentic Ai
127 Salesforce Argentina S.R.L.
Get a reply from this employer — a resume and cover letter tailored to exactly what they’re hiring for.
Ventajas ofrecidas por este puesto de trabajo
Descripción de la vacante
Pearster is seeking an Agentic AI Engineer to build generative AI workflows that automate cloud configuration baselines and remediation. You will design, implement, and productionize AI-powered solutions, collaborating with global teams to drive impact.
Required: 4+ years in software engineering on cloud infrastructure, 2+ years IaC and cloud pipelines, 2+ years with RAG and vector databases, and strong Python skills. Remote-friendly with USD compensation and flexible time off.
Formación
- 4+ years of software engineering on public cloud infrastructure.
- 2+ years of cloud deployment pipelines and Infrastructure as Code (IaC).
- 2+ years developing Agentic models using Retrieval‑Augmented Generation (RAG) and Vector databases.
- Ability to collaborate with globally distributed engineering teams.
Responsabilidades
- AI Acceleration: implement generative AI workflows using RAG, vector databases, and LLM APIs to automate cloud configuration baselines.
- Cloud Security Automation: develop AI-enabled drift detection, continuous discovery, and remediation workflows.
- Policy & IaC: generate and validate Terraform modules and Regula test cases for CI/CD pipelines.
- Design and integrate AI capabilities into existing applications and workflows to deliver value.
- Collaborate with cross-functional teams to share knowledge and best practices.
Conocimientos
Herramientas
Descripción del empleo
Spoiler: This is where your next big move begins.
At Pearster, we are hiring an AI Engineer to join our team. This is a 100% remote position where you will be responsible for designing, building, and implementing AI-powered solutions that solve real business challenges and create meaningful impact.
You will work with modern Artificial Intelligence technologies, including Generative AI, Large Language Models (LLMs), Machine Learning, and intelligent automation, collaborating with cross‑functional teams to transform ideas and business needs into scalable, production‑ready solutions.
We are looking for a curious, hands‑on, and innovative professional who enjoys experimenting with emerging technologies, solving complex problems, and turning the latest advances in AI into practical solutions.
- Build solutions leveraging Generative AI, Large Language Models (LLMs), and Machine Learning.
- Design, develop, and deploy AI‑powered applications and solutions.
- Develop and integrate AI agents, APIs, and intelligent automation workflows.
- Build solutions using RAG (Retrieval‑Augmented Generation), embeddings, vector databases, and prompt engineering.
- Integrate AI models and services from platforms such as OpenAI, Anthropic, Google, AWS, Azure, or similar providers.
- Develop prototypes and Proofs of Concept (POCs) and help transform successful experiments into production‑ready solutions.
- Evaluate and optimize AI solutions for accuracy, reliability, performance, scalability, and cost.
- Collaborate with Engineering, Product, and business stakeholders to identify opportunities where AI can create meaningful value.
- Integrate AI capabilities into existing applications, platforms, and workflows.
- Contribute to responsible AI practices, including security, privacy, monitoring, and appropriate use of AI systems.
- Stay up to date with emerging AI technologies, frameworks, tools, and industry best practices.
- Share knowledge and contribute to building AI capabilities and best practices across the organization.
- Strong programming skills, preferably in Python.
- Professional experience in Software Engineering, Artificial Intelligence, Machine Learning, Data Science, or a related technical field.
- Hands‑on experience building applications using Generative AI and Large Language Models (LLMs).
- Experience integrating APIs and developing backend services.
- Knowledge of prompt engineering, RAG, embeddings, vector databases, and AI agents.
- Familiarity with AI frameworks and tools such as LangChain, LlamaIndex, Hugging Face, or similar technologies.
- Experience working with AI APIs and platforms such as OpenAI, Anthropic, Google Gemini, or similar.
- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
- Understanding of Git, APIs, CI/CD, and modern software development practices.
- Strong analytical and problem‑solving skills.
- Ability to work independently in a fully remote environment.
- Strong communication and collaboration skills.
- Intermediate to advanced English level to collaborate effectively in an international environment.
We’re here to amplify your brilliance, not contain it.
- Work from anywhere with true flexibility and freedom.
- Earn in USD with compensation that matches your expertise.
- Recharge confidently with dedicated paid time off.
- Advance your career with fully covered international certifications.
- Access coworking spaces worldwide whenever you want a professional setup.
- Strengthen your English and expand your global reach.
- Connect and have fun with activities that unite our international team.
- Feel appreciated with personalized gifts and a thoughtful welcome kit.
- Grow our community and earn through our referral program.
At Pearster, your journey matters, and we’re here to help you go further than you imagined.
If you’re looking for a place to grow, make an impact, and work with people who care, we’d love to meet you!
We are looking for an Agentic AI Engineer to build generative AI workflows that automate cloud configuration baselines and remediation.
The mandatory requirements are 4+ years of software engineering experience on public cloud infrastructure, 2+ years with cloud deployment pipelines and Infrastructure as Code, 2+ years developing agentic models using RAG and vector databases, and the ability to partner with globally distributed engineering teams.
- 4+ years of software engineering experience developing applications and services hosted on public cloud infrastructure.
- 2+ years of experience with cloud infrastructure deployment pipelines and infrastructure as code (IaC).
- 2+ years of experience developing Agentic models (e.g., OpenAI, Anthropic) using Retrieval‑Augmented Generation (RAG) and Vector databases.
- Proven capability to partner with globally distributed inter-disciplinary engineering teams.
- Hands‑on experience with modern AI orchestration frameworks (LangChain, LangGraph).
- Hands‑on experience writing Rego policies (Open Policy Agent) or Regula test cases.
- Hands‑on experience with Terraform.
- Familiarity with cloud-native security services in Amazon Web Services, Azure, and Google Cloud Platform.
- Familiarity with PagerDuty, Atlassian Suite, and Service Now.
- AI Acceleration: implement generative AI workflows utilizing RAG, vector databases, and LLM APIs to automate the creation of cloud configuration baselines.
- Cloud Security Automation: develop AI‑enabled drift detection, continuous discovery, and gap analysis capabilities to accelerate response and remediation activities.
- Policy & Infrastructure as Code (IaC): generate and validate compliant Terraform modules, Rego policies (for Wiz Custom Configuration Rules), and Regula test cases for CI/CD pipelines.
- Professional growth: Mentorship, TechTalks, and personalized growth roadmaps.
- Competitive compensation: USD‑based pay with education, fitness, and team activity budgets.
- Exciting projects: Modern solutions with Fortune 500 and top product companies.
- Flextime: Flexible schedule with remote and office options.
- Toolkits RAG: LangChain Retrievers, LlamaIndex integrations.
Cloud AI Engineer, Google Cloud
Share Cloud AI Engineer, Google Cloud
Early
Experience completing work as directed, and collaborating with teammates; developing knowledge of relevant concepts and processes.
Share Cloud AI Engineer, Google Cloud
In most instances, this position requires in‑person interviews as part of the hiring process.
Minimum qualifications:
- Bachelor's degree in Computer Science or equivalent practical experience.
- Experience building machine learning solutions and working with technical customers.
- Experience designing cloud enterprise solutions and supporting customer projects to completion.
- Experience with data structures, algorithms, and software design.
- Experience coding in Python.
- Ability to communicate in English fluently to collaborate with other teams.
Preferred qualifications:
- Experience with recommendation engines, data pipelines, distributed machine learning, and deep learning frameworks.
- Experience with data analytics, data visualization techniques, and core Data Science methodologies.
- Experience in software development, professional services, or technical consulting for new technology initiatives.
- Knowledge of data warehousing (ETL/ELT), technical architectures, and big data environments (e.g., Hadoop, Spark).
- Knowledge of cloud computing, including virtualization, multi‑tenant infrastructures, and storage systems.
- Excellent customer‑facing communication and listening skills with expertise in architecting solutions.
About the job:
The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google's global network, web‑scale data centers, and software infrastructure.
As a Cloud AI Engineer, you will design and implement machine learning solutions for customer use cases, leveraging core Google products including TensorFlow, DataFlow, and Vertex AI. You will work with customers to identify opportunities to apply machine learning in their business, and travel to customer sites to deploy solutions and deliver workshops to educate and empower customers. Additionally, you will work closely with Product Management and Product Engineering to build and constantly drive excellence in our products.
In this role, you will be the Google Engineer working with Google's largest and most ambitious Cloud customers. Together with the team, you will support customer implementation of Google Cloud products through: architecture guidance, best practices, data migration, capacity planning, implementation, troubleshooting, monitoring, and much more.
Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise‑grade solutions that leverage Google's cutting‑edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Responsibilities:
- Be a trusted technical advisor to customers and solve complex machine learning challenges.
- Coach customers on the practical challenges in machine learning systems: feature extraction and feature definition, data validation, monitoring, and management of features and models.
- Work with Customers, Partners, and Google Product teams to deliver tailored solutions into production.
- Create and deliver best practice recommendations, tutorials, blog articles, and sample code.
- Travel up to 30% in‑region for meetings, technical reviews, and onsite delivery activities.
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents‑to‑be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy.
'/%3e%3cpath%20d='M101.744%2012.4726L102.894%2016.1947L99.0021%2013.2201L101.744%2012.4726ZM105.3%208.40937H100.488L99.0026%203.59473L97.5116%208.41047L92.7%208.40385L96.5965%2011.3834L95.1055%2016.1942L99.0021%2013.2196L101.408%2011.3834L105.3%208.40992V8.40937Z'%20fill='white'/%3e%3cdefs%3e%3clinearGradient%20id='paint0_linear_5593_1381'%20x1='90'%20y1='9.44471'%20x2='99'%20y2='9.44471'%20gradientUnits='userSpaceOnUse'%3e%3cstop%20stop-color='%2300AD70'/%3e%3cstop%20offset='0.998594'%20stop-color='%2300B67A'/%3e%3cstop%20offset='1'%20stop-color='%23DCDCE6'/%3e%3c/linearGradient%3e%3c/defs%3e%3c/svg%3e){kind=small}
