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Perplexity Jobs in Atlanta, GA (NOW HIRING)

As AI-powered discovery platforms--including Google AI Overviews, Google AI Mode, Gemini, ChatGPT, Claude, and Perplexity--become increasingly important in how software buyers research and evaluate ...

... Perplexity, Gemini, and Copilot. This is not just about gaining rankings. It is about gaining rankings that matter. Great targeting drives the right conversations. The role requires a deep ...

SEO Manager

Alpharetta, GA · On-site

$108K - $162K/yr

... Perplexity, Gemini, and Copilot. This is not just about gaining rankings. It is about gaining rankings that matter. Great targeting drives the right conversations. The role requires a deep ...

Showing results 21-27

Perplexity information

What is a perplexity job?

Perplexity jobs typically refer to roles at Perplexity AI, a company specializing in artificial intelligence-powered search engines and conversational AI tools. Employees may work in a variety of positions such as software engineering, research, product management, and data science. Perplexity AI is known for its focus on creating advanced, user-friendly AI systems that help people access and understand information more easily. Working at Perplexity often involves collaborating on innovative projects, leveraging the latest AI technologies, and contributing to the development of cutting-edge products in the AI space.

What are the key skills and qualifications needed to thrive as a Perplexity AI Engineer?

To thrive as a Perplexity AI Engineer, you need a strong background in computer science, machine learning, and natural language processing, often supported by a relevant degree and hands-on project experience. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and version control systems like Git is essential. Strong problem-solving abilities, collaboration, and effective communication help you excel in multidisciplinary teams and adapt to evolving technologies. These skills are crucial for developing advanced AI solutions and ensuring they perform reliably and ethically in real-world applications.

What are the common challenges faced by a data scientist when working on machine learning projects within a cross-functional team?

Data Scientists often encounter challenges such as aligning project goals across departments, ensuring data quality, and effectively communicating complex technical concepts to non-technical stakeholders. Collaborating with product managers, engineers, and business analysts requires strong interpersonal skills and adaptability. Additionally, balancing experimentation with project deadlines and integrating models into production systems are key hurdles. Navigating these challenges successfully can lead to impactful solutions and professional growth.
What are popular job titles related to Perplexity jobs in Atlanta, GA? For Perplexity jobs in Atlanta, GA, the most frequently searched job titles are:
What job categories do people searching Perplexity jobs in Atlanta, GA look for? The top searched job categories for Perplexity jobs in Atlanta, GA are:
What cities near Atlanta, GA are hiring for Perplexity jobs? Cities near Atlanta, GA with the most Perplexity job openings:
Infographic showing various Perplexity job openings in Atlanta, GA as of August 2026, with employment types broken down into 1% Internship, 92% Full Time, 4% Part Time, and 3% Contract. Highlights an 81% Physical, 3% Hybrid, and 16% Remote job distribution.

Principal AI App Dev Engineer - Vice President

Morgan Stanley

Alpharetta, GA • On-site

Full-time

Posted 5 days ago


Morgan Stanley rating

8.4

Company rating: 8.4 out of 10

Based on 155 frontline employees who took The Breakroom Quiz

30th of 150 rated financial services


Job description

We are seeking an innovative Agentic AI Forward Deployed Engineer (FDE) to build the next generation of autonomous AI systems.

In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities. This is a Lead Technical Product Owner position at Vice President level, which is part of the job family responsible for defining the product vision, prioritizing features, and ensuring the successful delivery of high-quality technical solutions.

What you'll do in the role:

You will design multi-agent architectures that move beyond simple question-answering, enabling AI systems to break down problems, use external APIs, iterate through feedback loops, and operate independently to drive measurable business impact. You will enable transition of engineering teams from "developers" into "system architects". Instead of writing raw code, your focus will be on creating coding/testing agents and setting up "human-in-the-loop" or autonomous feedback harnesses and scaling these capabilities across the organization.

  • Agent Architecture: Design and build multi-agent frameworks. Implement human-in-the-loop handoffs, logging, and guardrails to ensure agents comply with data protection and governance standards

  • Agent-first engineering loop: Design and build agent skills, tools for desktop coding agents to improve engineering productivity. accelerate SDLC, reduce defects / rework and improve delivery quality through agentic workflows

  • Evangelism & Coaching: Act as a trusted advisor, coaching engineering squads on effectively prompting, reviewing, and evaluating agent outputs. Drive enterprise AI adoption safely

  • Hands-on programming to develop high performance code, implement application frameworks and develop prototypes to showcase new technology opportunities

What you'll bring to the role:

  • Overall experience between 7-12 years. Minimum 3 years in a role as Lead Engineer/Technical Architect designing for Distributed applications, Microservices architecture, Fault tolerance and recovery, Performance Engineering, Scaling, Low latency application design, Asynchronous programming

  • Languages - Proficient in atleast one of Java or C# or Typescript/ReAct. Intermediate level Python

  • Infrastructure - Comfortable shipping production grade systems on Hybrid cloud infra (Docker, K8s, AWS or Azure).

  • AI Foundational: LLM fundamentals (encoder, decoder, and encoder-decoder models; fine-tuning vs. prompt-tuning vs. LoRA); Prompt engineering (zero-shot, few-shot, and chain-of-thought prompting; prompt testing and optimization); Vector databases (for embedding storage and similarity search); Embedding models (selection, generation, and dimensionality considerations).

  • Agentic SDLC Harness: Design specialized SDLC agent harness loops (requirements, architecture, coding, and testing agents) and manage the interaction and context-sharing between them. Platform Integration (Embed agentic workflows natively into the existing developer ecosystem, CI/CD pipelines, version control, and test harnesses).

  • Copilot/Open AI Codex/Claude Code: Leverage hands-on familiarity with Copilot/OpenAI Codex or Claude Code to optimize model prompting, tool usage, context construction, developing custom skills and system prompts to improve task solve rates

  • LangGraph/OpenAI SDK/Claude SDK: Build autonomous AI agents with Conversational state, Tool calling, Sub agent orchestration

Secondary Skills
  • Agentic AI: Autonomous agent concepts (multi-step reasoning, goal decomposition, self-reflection loops, and replanning strategies); Tool-oriented execution (agents calling APIs, executing scripts, interacting with knowledge bases, or triggering workflows); Safety and governance (guardrails, grounding, hallucination prevention, and ethical AI use); Agent evaluation (reasoning accuracy, success/failure patterns, Efficiency metrics and Evaluation metrics such as accuracy, F1-score, or perplexity); MCP server concepts (architecture for agent communication and orchestration, request/response flows, streaming data, multi-agent coordination, and contextual state management); Agentic AI architecture internals (planner, executor, memory store, tool registry, event loop, orchestration layers, schedulers, task prioritization, failure recovery, and multi-agent collaboration patterns).

  • RAG: RAG architecture (retrieval pipelines, context injection, and grounding of LLM outputs); document chunking and indexing (splitting strategies, token limits, and indexing performance); Query processing (rewriting, filtering, and ranking retrieved documents); Evaluation and latency optimization (measuring retrieval accuracy and reducing end-to-end response time).

WHAT YOU CAN EXPECT FROM MORGAN STANLEY:

At Morgan Stanley, we raise, manage and allocate capital for our clients - helping them reach their goals. We do it in a way that's differentiated - and we've done that for 90 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren't just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you'll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There's also ample opportunity to move about the business for those who show passion and grit in their work.

To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser.

Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background. Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents.

Our workforce reflects a broad cross-section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.

For more information, please visit: https://www.morganstanley.com/people-opportunities/eeo.


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