Job Description

Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

About Team:

Digital Engineering is Thermo Fisher's "

Software Engineering

" center of excellence. We build cloud computing services, products and Platforms that the scientific community demands. Using the emerging technologies with the potential to significantly change lab workflows and facilitate access to powerful data analysis techniques. Our division serves as an extension of Thermo Fisher's Software R&D teams while enhancing our responsiveness and attention in enabling our customers to make the world healthier, cleaner and safer. Thermo Fisher was built to serve society and that sense of purpose will continue to enhance innovation and scientific advancement. We are committed to diversity in our workforce and is proud to be an equal opportunity employer


We apply industry standard methodologies to the design, development, and deployment of world- class software products built to demonstrate the power and scalability of the cloud.

Roles & Responsibilities:

Purpose:

The Software Staff Engineer provides software and systems architectural and design leadership to multiple Software Development Scrum Teams delivering a Gen AI Solution.


As a

Lead Developer

, this individual will actively contribute to the

architecture

,

design

, and

development

of new features, integrating

Generative AI

systems to enhance functionality. The role involves working with

AI frameworks

and models, ensuring seamless integration with existing product offerings. In addition to that, the role also demands to lead, empower, mentor, and provide ample guidance to the other team members with respect to technical challenges.

Responsibilities:

Provide software and systems architectural and design leadership to team of engineers. Design and implement cloud service and software architecture for new products, and extensions to existing products. Be the team's "go-to" person for architectural, design and implementation related questions and provide guidance. Active contribution in solution analysis of requirements Able to understand, articulate and challenge the requirements Provides guidance regarding design activity to other programmers on technical aspects relating to the project. Proactively looks for ways and patterns to continuously automate feature testing with measurable and tangible goals Is authentic, transparent and leads by example, holding self and others accountable. Inspires, motivates and collaborates with others Anticipates needs and problems while creating solutions. Is willing to ask difficult questions and do things differently. Greets challenge and change as opportunity A highly motivated fast learner who can self-start and "determine what needs figuring out" Actively participates in development community of practices in sharing and learning standard processes, leads initiatives within the community and involve in other organization initiatives Excellent verbal and written communication skills. Ability to effectively document artifacts and processes then explain them to others

Candidate Requirement:

Education

: Bachelors in Engineering or Masters in Computer Science with 10+ years of extensive experience.

Mandatory Skills, Knowledge, and Experience:

Python Development Experience:

Minimum 6 years of proven experience in

Python

development, with a strong emphasis on

backend

development, including creating RESTful APIs, working with libraries like

FastAPI

for high-performance web services.

Generative AI (Gen AI) & OpenAI Integration:

Hands-on experience with

Generative AI

frameworks and APIs, including

OpenAI

models for generating human-like responses, completing tasks, and automating processes. Knowledge of how to effectively integrate these models into applications.

API Development & Integration:

Extensive experience in building and maintaining

REST APIs

using

FastAPI

, ensuring efficient communication between different services and applications. Familiarity with

authentication

,

authorization

, and

API rate-limiting

.

Data Engineering & Processing:

Strong skills in

data engineering

, including data extraction, transformation, and loading (ETL) processes. Expertise in

Pandas

for data manipulation, analysis, and handling large datasets.

LLM (Large Language Model) Prompt Engineering:

Experience in

prompt engineering

for

LLMs

. Ability to design and optimize prompts for specific use cases to extract relevant, high-quality outputs.

Python Data Science Libraries:

Strong proficiency in

Pandas

,

NumPy

, and other data analysis libraries to process and manipulate large volumes of data. Experience in generating data insights and performing statistical analyses.

Version Control & CI/CD:

Proficient in using

Git

for version control and familiar with

CI/CD pipelines

for automated testing and deployment processes.

Scrum and Agile Methodologies:

3+ years of experience with

Scrum

or Agile-based software development methodologies, with a focus on iterative development and collaboration.

Testing and Automation:

Experience in

unit testing

,

integration testing

, and

automated testing

using frameworks like

pytest

and

unittest

to ensure code quality and reliability.

Communication & Documentation:

Excellent verbal and written communication skills, capable of detailing code, technical processes, and explaining them to both technical and non-technical collaborators.

Non-Functional Requirements (NFR):

Experience in defining and implementing

Non-Functional Requirements

such as

performance

optimizations,

scalability

, and

security

in data-driven applications.

Nice to Have Skills, Knowledge, and Experience:

Cloud Services & Deployment:

Experience with

cloud platforms

like

AWS

or

GCP

, specifically related to

data storage

,

serverless computing

, and

scalable APIs

.

Data Pipeline Tools:

Familiarity with data pipeline tools like

Apache Airflow

,

Apache Kafka

, or similar platforms for managing and orchestrating data workflows.

Machine Learning & AI Frameworks:

Experience with machine learning libraries such as

scikit-learn

,

TensorFlow

,

PyTorch

, or similar, particularly in building and training models for data-driven applications.

Code Quality & Analysis Tools:

Experience with

SonarQube

,

ESLint

, or similar tools for

code quality analysis

, ensuring maintainability and scalability of the codebase.