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Performance Engineering Manager Jobs in Indiana (NOW HIRING)

WHAT YOU GET TO DO As a Shift Engineering Manager, you will be part of a team that works to ... Achieve and maintain performance metrics in line with contractual expectations (output, response ...

Engineering Manager - Facility Projects

Princeton, IN · On-site

$109.90K/yr

The Engineering Manager will ensure projects are planned and executed to meet quality, cost ... Ensure team performance meets or exceeds project KPIs (Safety, Cost, Schedule, Quality) across the ...

CTIO AI Engineering Manager

Indianapolis, IN · On-site

$73.50K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... and managing performance to deliver on client expectations. With your growing knowledge of how ...

Provides hiring, promotion and disciplinary action recommendations, as well as performance ... Influences more senior management in the development of staffing plans and projections and ...

Material Handler

Pittsboro, IN · On-site

$16 - $19.25/hr

Fleece Performance Engineering is a leading manufacturer of after-market diesel performance ... Coordinate with machine shop operators and the Machine Shop Manager to prepare and deliver bins of ...

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Evaluate the performance and development of technical staff. * Collaborate with the department managers to develop, evaluate, and implement new policies and procedures which reflect best engineering ...

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Showing results 1-20

Performance Engineering Manager information

See Indiana salary details

$38.1K

$94.7K

$146.1K

How much do performance engineering manager jobs pay per year?

As of May 31, 2026, the average yearly pay for performance engineering manager in Indiana is $94,707.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,300.00 and $119,900.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Performance Engineering Manager, and why are they important?

To thrive as a Performance Engineering Manager, you need a solid background in software engineering, performance testing, and systems optimization, often supported by a degree in computer science or a related field. Familiarity with tools such as JMeter, LoadRunner, APM solutions, and cloud platforms is typically required, along with knowledge of performance monitoring and automation frameworks. Strong leadership, analytical thinking, and effective communication are critical soft skills for guiding teams and collaborating across departments. These skills ensure the delivery of high-performing software solutions, drive continuous improvement, and help meet business scalability and reliability goals.

How does a Performance Engineering Manager typically collaborate with development and operations teams to ensure optimal system performance?

A Performance Engineering Manager works closely with both development and operations teams to establish performance benchmarks, identify potential bottlenecks early in the software development lifecycle, and implement performance testing protocols. This role often involves facilitating regular meetings to review performance metrics, coordinating load and stress testing efforts, and providing actionable feedback for code optimization. By fostering open communication and aligning goals across teams, the Performance Engineering Manager ensures that performance considerations are integrated into every stage of product development and deployment.

What are Performance Engineering Managers?

Performance Engineering Managers are professionals responsible for overseeing teams that ensure software applications and systems operate efficiently and reliably under expected workloads. They focus on optimizing performance, scalability, and stability by identifying bottlenecks, setting performance standards, and implementing best practices. These managers collaborate closely with development, QA, and operations teams to deliver high-performing products, often leveraging tools for monitoring and analysis. Their role also includes mentoring engineers, managing project timelines, and communicating performance goals to stakeholders.

What is the difference between Performance Engineering Manager vs Software Development Manager?

AspectPerformance Engineering ManagerSoftware Development Manager
Primary FocusOptimizing system performance, scalability, and reliabilityOverseeing software development processes and team management
Required SkillsPerformance testing, monitoring tools, system architectureSoftware design, project management, coding
Work EnvironmentCollaboration with QA, DevOps, and infrastructure teamsLeading development teams, coordinating projects
Industry UsageTech companies, cloud services, enterprise softwareSoftware firms, tech startups, enterprise applications

The Performance Engineering Manager focuses on ensuring software and systems perform efficiently and reliably, often working closely with infrastructure and QA teams. In contrast, the Software Development Manager oversees the entire software development lifecycle, managing developers and project timelines. Both roles require technical expertise but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Performance Engineering jobs in Indiana? The most popular types of Performance Engineering jobs in Indiana are:
What are popular job titles related to Performance Engineering Manager jobs in Indiana? For Performance Engineering Manager jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Performance Engineering Manager jobs in Indiana look for? The top searched job categories for Performance Engineering Manager jobs in Indiana are:
What cities in Indiana are hiring for Performance Engineering Manager jobs? Cities in Indiana with the most Performance Engineering Manager job openings:
Infographic showing various Performance Engineering Manager job openings in Indiana as of May 2026, with employment types broken down into 1% As Needed, 96% Full Time, 2% Part Time, and 1% Contract. Highlights an 74% Physical, 4% Hybrid, and 22% Remote job distribution, with an average salary of $94,707 per year, or $45.5 per hour.
AI Engineering Manager - SFL Scientific

AI Engineering Manager - SFL Scientific

Deloitte

Indianapolis, IN • On-site

Other

Posted 10 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

58th of 138 rated financial services


Job description

Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey-before, during, and after any major transformational projects or transactions.
Are you passionate about leading the charge in emerging technologies? Do you want to join an award-winning team offering diverse opportunities, from account executives and data scientists to AI strategists, machine learning experts, and data engineers? If so, the AI Engineering Manager at SFL Scientific might be the perfect fit. SFL Scientific, a Deloitte Business, is part of our broader Strategy Offering within the Strategy & Transactions practice. Our specialized team brings together key capabilities to design integrated solutions that drive transformational change for our clients. Join us to expand your technical career through leadership, consulting, and becoming an industry leader in the AI engineering community.

Recruiting for this role ends on 8/31/2026.
Work You'll Do
As an AI Engineering Manager you will support the design, development, and deployment of novel AI applications across healthcare, life sciences, manufacturing, consumer, energy, and other sectors. You will lead client engagements and design and deliver architecture for complex AI and R&D type problems. AI Engineering Manager are responsible for developing design patterns, infrastructure, and engineering resources by understanding business and use case priorities, defining the data strategy, and leading application deployment to solve our clients' use cases. They work cross-functionally with data scientists, DevOps and data engineers, project managers, and industry experts to develop robust AI platforms and cloud solutions.
In our consultative approach, we are platform agnostic and committed to accelerating the development of innovative AI solutions for our clients with the best possible tools; this spans all relevant technologies from on-prem and cloud deployment, high performance computing, automation, DevOps, LLM/MLOps, data engineering while streamlining IT and infrastructure. Key responsibilities include but are not limited to:

  • Work with clients to design, develop, and deploy new architectures to support machine learning & automation applications
  • Leverage advanced technical skills in modern data architecture, data science engineering, data transformation, and management of structured and unstructured data sources using cloud computing or on-prem technologies
  • Design and lead development on scalable, high-performance data architecture solutions that supports both the client business as well as AI/GenAI use cases
  • Support and enhance data architecture, and data pipelines, and define database schemas (Graph, SQL, NoSQL) to develop algorithm scalability and deployment based on agile business priorities and initiatives
  • Participate in architectural and deployment discussions to ensure solutions are designed for successful scale, security, and high availability in the cloud or on prem
  • Adopt best engineering practices in automation, HPC and AI/GenAI infrastructure and design patterns
  • Define and lead technology proof of concepts to ensure feasibility of new data and cloud technology solutions
  • Display strong thought leadership and execution in pursuit of modern data architecture principles and technology modernization
  • Mentor, motivate, and coach junior members on technical best practices and inspire professional development

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

The Team

Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.
Specifically, SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.
Qualifications


Required:

  • Bachelor's degree in a STEM field (Computer Science, Engineering, Physics, etc.)
  • 6+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment
  • 6+ years of experience in designing cloud solutions and supporting production projects, including hands-on experience with AWS services (or Azure, GCP equivalents)
  • 6+ years of programming experience with Linux Shell/CLI, Python, SQL, PowerShell, etc.
  • 4+ years of experience managing teams in technical delivery and delivering complex and critical projects
  • 4+ years of experience in DevOps and leveraging CI/CD services: Puppet, Ansible, Chef, Airflow, Terraform, Jenkins etc.
  • 4+ years of experience with database development and ETL/ELT pipelines (relational, NoSQL, Neo4j)
  • 3+ years of experience with deployment and optimization: Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLflow, Kafka, etc.
  • Live within commuting distance to one of Deloitte's consulting offices
  • Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available


Preferred:

  • Master's degree in Computer Science, Engineering, Physics, etc. or related STEM field
  • AWS/Azure Certifications (AWS/Azure Certified: SysOps Administrator, DevOps Engineer, Solutions Architect)
  • 2+ years of experience with GPU computing (CUDA, OpenCL) and HPC system software stack

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey-before, during, and after any major transformational projects or transactions.
Are you passionate about leading the charge in emerging technologies? Do you want to join an award-winning team offering diverse opportunities, from account executives and data scientists to AI strategists, machine learning experts, and data engineers? If so, the AI Engineering Manager at SFL Scientific might be the perfect fit. SFL Scientific, a Deloitte Business, is part of our broader Strategy Offering within the Strategy & Transactions practice. Our specialized team brings together key capabilities to design integrated solutions that drive transformational change for our clients. Join us to expand your technical career through leadership, consulting, and becoming an industry leader in the AI engineering community.

Recruiting for this role ends on 8/31/2026.
Work You'll Do
As an AI Engineering Manager you will support the design, development, and deployment of novel AI applications across healthcare, life sciences, manufacturing, consumer, energy, and other sectors. You will lead client engagements and design and deliver architecture for complex AI and R&D type problems. AI Engineering Manager are responsible for developing design patterns, infrastructure, and engineering resources by understanding business and use case priorities, defining the data strategy, and leading application deployment to solve our clients' use cases. They work cross-functionally with data scientists, DevOps and data engineers, project managers, and industry experts to develop robust AI platforms and cloud solutions.
In our consultative approach, we are platform agnostic and committed to accelerating the development of innovative AI solutions for our clients with the best possible tools; this spans all relevant technologies from on-prem and cloud deployment, high performance computing, automation, DevOps, LLM/MLOps, data engineering while streamlining IT and infrastructure. Key responsibilities include but are not limited to:

  • Work with clients to design, develop, and deploy new architectures to support machine learning & automation applications
  • Leverage advanced technical skills in modern data architecture, data science engineering, data transformation, and management of structured and unstructured data sources using cloud computing or on-prem technologies
  • Design and lead development on scalable, high-performance data architecture solutions that supports both the client business as well as AI/GenAI use cases
  • Support and enhance data architecture, and data pipelines, and define database schemas (Graph, SQL, NoSQL) to develop algorithm scalability and deployment based on agile business priorities and initiatives
  • Participate in architectural and deployment discussions to ensure solutions are designed for successful scale, security, and high availability in the cloud or on prem
  • Adopt best engineering practices in automation, HPC and AI/GenAI infrastructure and design patterns
  • Define and lead technology proof of concepts to ensure feasibility of new data and cloud technology solutions
  • Display strong thought leadership and execution in pursuit of modern data architecture principles and technology modernization
  • Mentor, motivate, and coach junior members on technical best practices and inspire professional development

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

The Team

Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.
Specifically, SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.
Qualifications


Required:

  • Bachelor's degree in a STEM field (Computer Science, Engineering, Physics, etc.)
  • 6+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment
  • 6+ years of experience in designing cloud solutions and supporting production projects, including hands-on experience with AWS services (or Azure, GCP equivalents)
  • 6+ years of programming experience with Linux Shell/CLI, Python, SQL, PowerShell, etc.
  • 4+ years of experience managing teams in technical delivery and delivering complex and critical projects
  • 4+ years of experience in DevOps and leveraging CI/CD services: Puppet, Ansible, Chef, Airflow, Terraform, Jenkins etc.
  • 4+ years of experience with database development and ETL/ELT pipelines (relational, NoSQL, Neo4j)
  • 3+ years of experience with deployment and optimization: Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLfl...

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